| 1. |
- Alves, Dimas I, et al.
(författare)
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A Statistical Analysis for Wavelength-Resolution SAR Image Stacks
- 2020
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Ingår i: IEEE Geoscience and Remote Sensing Letters. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 1545-598X .- 1558-0571. ; 17:2, s. 227-231
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Tidskriftsartikel (refereegranskat)abstract
- This letter presents a clutter statistical analysis for stacks of wavelength-resolution synthetic aperture radar (SAR) images. Each image stack consists of SAR images generated by the same sensor, using the same flight track illuminating the same scene but with a time separation between the illuminations. We test three candidate statistical distributions for time changes in the stack, namely, Rician, Rayleigh, and log-normal. The tests results reveal that the Rician distribution is a very good candidate for modeling stack of wavelength-resolution SAR images, where 98.59 & x0025; of the tested samples passed the Anderson-Darling (AD) goodness-of-fit test. Also, it is observed that the presence of changes in the ground scene is related to the tested samples that have failed in the AD test for the Rician distribution hypothesis.
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| 2. |
- Alves, Dimas irion, et al.
(författare)
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Change Detection Method for Wavelength-Resolution SAR Images Based on Bayes’ Theorem : An Iterative Approach
- 2023
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Ingår i: IEEE Access. - Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE). - 2169-3536. ; 11, s. 84734-84743
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents an iterative change detection (CD) method based on Bayes’ theorem for very high-frequency (VHF) ultra-wideband (UWB) SAR images considering commonly used clutter-plus-noise statistical models. The proposed detection technique uses the information of the detected changes to iteratively update the data and distribution information, obtaining more accurate clutter-plus-noise statistics resulting in false alarm reduction. The Bivariate Rayleigh and Bivariate Gaussian distributions are investigated as candidates to model the clutter-plus-noise, and the Anderson-Darling goodness-of-fit test is used to investigate three scenarios of interest. Different aspects related to the distributions are discussed, the observed mismatches are analyzed, and the impact of the distribution chosen for the proposed iterative change detection method is analyzed. Finally, the proposed iterative method performance is assessed in terms of the probability of detection and false alarm rate and compared with other competitive solutions. The experimental evaluation uses data from real measurements obtained using the CARABAS II SAR system. Results show that the proposed iterative CD algorithm performs better than the other methods. Author
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| 3. |
- Alves, Dimas, I, et al.
(författare)
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Incoherent Change Detection Methods for Wavelength-Resolution SAR Image Stacks Based on Masking Techniques
- 2020
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Ingår i: 2020 IEEE National Radar Conference - Proceedings. - : IEEE. - 9781728189420
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Konferensbidrag (refereegranskat)abstract
- This paper presents two incoherent change detection methods for wavelength-resolution synthetic aperture radars (SAR) image stacks based on masking techniques. The first technique proposed is the Simple Masking Detection (SMD). This method uses the statistical behavior of pixels-sets in the image stack to create a binary mask, which is used to remove pixels that are not related to changes in a surveillance image from the same interest region. The second technique is the Multiple Concatenated Masking Detection (MCMD), which produces a more selective mask than the SMD by concatenating multiple masks from different image stacks. The MCMD can be used in specific applications where multiple stacks share common patterns of target deployments. Both proposed techniques were evaluated using 24 incoherent SAR images obtained by the CARABAS II system. The experimental results revealed that the proposed detection methods have better performance in terms of probability of detection and false alarm rate when compared with other change detection techniques, especially for high detection probabilities scenarios.
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| 4. |
- Alves, Dimas I., et al.
(författare)
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Neyman-Pearson Criterion-Based Change Detection Methods for Wavelength-Resolution SAR Image Stacks
- 2022
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Ingår i: IEEE Geoscience and Remote Sensing Letters. - : Institute of Electrical and Electronics Engineers Inc.. - 1545-598X .- 1558-0571. ; 19
-
Tidskriftsartikel (refereegranskat)abstract
- This letter presents two new change detection (CD) methods for synthetic aperture radar (SAR) image stacks based on the Neyman-Pearson criterion. The first proposed method uses the data from wavelength-resolution images stack to obtain background statistics, which are used in a hypothesis test to detect changes in a surveillance image. The second method considers a priori information about the targets to obtain the target statistics, which are used together with the previously obtained background statistics, to perform a hypothesis test to detect changes in a surveillance image. A straightforward processing scheme is presented to test the proposed CD methods. To assess the performance of both proposed methods, we considered the coherent all radio band sensing (CARABAS)-II SAR images. In particular, to obtain the temporal background statistics required by the derived methods, we used stacks with six images. The experimental results show that the proposed techniques provide a competitive performance in terms of probability of detection and false alarm rate compared with other CD methods. CCBY
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| 5. |
- Alves, Dimas I, et al.
(författare)
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Statistical Analysis for Wavelength-Resolution SARImage Stacks : New Case Studies
- 2020
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Ingår i: XXXVIII SIMPÓSIO BRASILEIRO DE TELECOMUNICAÇÕES E PROCESSAMENTO DE SINAIS.
-
Konferensbidrag (refereegranskat)abstract
- This paper presents new case studies for thestatistical analysis for wavelength resolution SAR image stacks.The statistical analysis considers the Anderson-Darling goodnessof-fit test in a set of pixel samples from the same position obtainedfrom a SAR image stack. The test is applied in wavelengthresolution SAR image stacks. The present work consists of twocase studies based on the use of multiple-pass stacks and TypeI error using the False Discovery Rate controlling procedures.In addition, an application scenario is presented for the studiedscenarios.
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| 6. |
- Alves, Dimas Irion, et al.
(författare)
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Wavelength-Resolution SAR Change Detection Using Bayes' Theorem
- 2020
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Ingår i: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 1939-1404 .- 2151-1535. ; 13, s. 5560-5568
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Tidskriftsartikel (refereegranskat)abstract
- This article presents Bayes' theorem for wavelength-resolution synthetic aperture radar (SAR) change detection method development. Different change detection methods can be derived using Bayes' theorem in combination with the target model, clutter-plus-noise model, iterative implementation, and noniterative implementation. As an example of the Bayes' theorem use for wavelength-resolution SAR change detection method development, we propose a simple change detection method with a clutter-plus-noise model and noniterative implementation. In spite of simplicity, the proposed method provides a very competitive performance in terms of probability of detection and false alarm rate. The best result was a probability of detection of $\text{98.7}\%$ versus a false alarm rate of one per square kilometer.
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| 7. |
- Araujo, Gustavo F., et al.
(författare)
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A Tailored cGAN SAR Synthetic Data Augmentation Method for ATR Application
- 2023
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Ingår i: Proceedings of the IEEE Radar Conference. - : Institute of Electrical and Electronics Engineers (IEEE). - 9781665436694
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Konferensbidrag (refereegranskat)abstract
- This article proposes a method to simulate Synthetic Aperture Radar (SAR) targets for specific incidence and azimuth angles. Images synthesized by Electromagnetic Computing (EMC) are used to train a Conditional Generative Adversarial Network (cGAN). Two synthetic image chips of the same class and incidence angle, separated by two degrees in azimuth, are used as input to the cGAN. The cGAN predicts the image of the same class and incidence angle whose azimuth angle corresponds to the bisector of the two input chips. An evaluation using the SAMPLE dataset was performed to verify the quality of the image prediction. Running through a total of 100 training epochs, the cGAN converges, reaching the best Mean Squared Error (MSE) after 77 epochs. The results demonstrate that the proposed method is promising for Automatic Target Recognition (ATR) applications. © 2023 IEEE.
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| 8. |
- Araujo, Gustavo F., et al.
(författare)
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Assessment of preprocessing techniques in a model-based automatic target recognition algorithm for the SAMPLE dataset
- 2022
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Ingår i: Image and Signal Processing for Remote Sensing XXVIII 2022. - : SPIE - International Society for Optical Engineering. - 9781510655379
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Konferensbidrag (refereegranskat)abstract
- This article investigates basic preprocessing techniques to improve classification accuracy in the context of Automatic Target Recognition (ATR) of non-cooperative targets in Synthetic Aperture Radar (SAR) images. Preprocessing techniques are considered in synthetic data providing different inputs to a model-based classification algorithm. Experiments with preprocessing techniques such as area reduction, morphological transformations, and speckle filtering were run using ten target classes of the SAMPLE dataset. The classification is performed in measure data using scattering centers as features. The results reveal that the original image without any preprocessing techniques reached the best classification performance. However, investigations with other classifiers that use different features may benefit from such preprocessing techniques. © 2022 SPIE.
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| 9. |
- Araujo, Gustavo F., et al.
(författare)
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Non-Cooperative SAR Automatic Target Recognition Based on Scattering Centers Models
- 2022
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Ingår i: Sensors. - : MDPI. - 1424-8220. ; 22:3
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Tidskriftsartikel (refereegranskat)abstract
- This article proposes an Automatic Target Recognition (ATR) algorithm to classify non-cooperative targets in Synthetic Aperture Radar (SAR) images. The scarcity or nonexistence of measured SAR data demands that classification algorithms rely only on synthetic data for training purposes. Based on a model represented by the set of scattering centers extracted from purely synthetic data, the proposed algorithm generates hypotheses for the set of scattering centers extracted from the target under test belonging to each class. A Goodness of Fit test is considered to verify each hypothesis, where the Likelihood Ratio Test is modified by a scattering center-weighting function common to both the model and target. Some algorithm variations are assessed for scattering center extraction and hypothesis generation and verification. The proposed solution is the first model-based classification algorithm to address the recently released Synthetic and Measured Paired Labeled Experiment (SAMPLE) dataset on a 100% synthetic training data basis. As a result, an accuracy of 91.30% in a 10-target test within a class experiment under Standard Operating Conditions (SOCs) was obtained. The algorithm was also pioneered in testing the SAMPLE dataset in Extend Operating Conditions (EOCs), assuming noise contamination and different target configurations. The proposed algorithm was shown to be robust for SNRs greater than −5 dB. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
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| 10. |
- Araujo, Gustavo F., et al.
(författare)
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Synthetic SAR Data Generator Using Pix2pix cGAN Architecture for Automatic Target Recognition
- 2023
-
Ingår i: IEEE Access. - : Institute of Electrical and Electronics Engineers (IEEE). - 2169-3536. ; 11, s. 143369-143386
-
Tidskriftsartikel (refereegranskat)abstract
- Synthetic Aperture Radar (SAR) technology has unique advantages but faces challenges in obtaining enough data for noncooperative target classes. We propose a method to generate synthetic SAR data using a modified pix2pix Conditional Generative Adversarial Networks (cGAN) architecture. The cGAN is trained to create synthetic SAR images with specific azimuth and elevation angles, demonstrating its capability to closely mimic authentic SAR imagery through convergence and collapsing analyses. The study uses a model-based algorithm to assess the practicality of the generated synthetic data for Automatic Target Recognition (ATR). The results reveal that the classification accuracy achieved with synthetic data is comparable to that attained with original data, highlighting the effectiveness of the proposed method in mitigating the limitations imposed by noncooperative SAR data scarcity for ATR. This innovative approach offers a promising solution to craft customized synthetic SAR data, ultimately enhancing ATR performance in remote sensing.
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| 11. |
- Batra, A., et al.
(författare)
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Analysis of Surface Roughness with 3D SAR Imaging at 1.5 THz
- 2023
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Ingår i: 2023 48TH INTERNATIONAL CONFERENCE ON INFRARED, MILLIMETER, AND TERAHERTZ WAVES, IRMMW-THZ. - : Institute of Electrical and Electronics Engineers (IEEE). - 9798350336603
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Konferensbidrag (refereegranskat)abstract
- The expansion of the synthetic aperture radar (SAR) to the emerging THz spectrum has enabled a new era of applications in the areas of automobile, security, non-destructive testing, and material characterization. Thanks to the sub-mm wavelength, extraction of material surface properties is possible and of significant interest for the THz SAR applications. The properties define the surface scattering behavior, which is relational to the applied frequency. This study focuses on surface classification. We evaluate the scattering behavior of a rough surface and a smooth surface at 1.5 THz based on a SAR processing sequence that is introduced in this paper. First, we form the 3D SAR images of the metallic objects and then evaluate the surface properties based on the variation in the energy reflected by the object's surface.
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| 12. |
- Batra, Aman, et al.
(författare)
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Experimental analysis of high resolution indoor THz SAR imaging
- 2020
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Ingår i: WSA 2020 - 24th International ITG Workshop on Smart Antennas. - : VDE Verlag GmbH. - 9783800752003
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Konferensbidrag (refereegranskat)abstract
- Synthetic Aperture Radar (SAR) technology is most commonly used in the frequency span of sub-30 GHz which provides the spatial resolution in the range of sub-cm. This technology is being extended to higher frequencies such as millimeter wave and THz region to achieve higher resolution in the range of sub-mm. This expands the SAR applications for material characterization, classification and sub-mm localization. However, the region is suitable for short propagation distance such as an indoor environment. Therefore, to investigate the achieved resolution and quality of the SAR images at THz, an indoor SAR testbed based on vector network analyzer has been setup for the measurements. This paper explains the indoor SAR geometry and describes the associated testbed along with the system parameters. The measurements are performed at a centre frequency of 275 GHz with a bandwidth of 110 GHz. The measurement results are analyzed for the theoretical resolution with the Backprojection Algorithm and the findings are presented in this paper. The sub-mm spatial resolution imaging of two small size metallic objects are performed. © WSA 2020.
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| 13. |
- Batra, Aman, et al.
(författare)
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Sub-mm Resolution Indoor THz Range and SAR Imaging of Concealed Object
- 2020
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Ingår i: 2020 IEEE MTT-S International Conference on Microwaves for Intelligent Mobility, ICMIM 2020. - : Institute of Electrical and Electronics Engineers Inc.. - 9781728167558
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Konferensbidrag (refereegranskat)abstract
- In radar systems, the frequency range is being extended to high frequencies such as THz for sub-mm resolution. The spectrum offers high resolution but on the contrary, propagation distance and penetration depth are limited because of smaller wavelength. It suffers from higher atmospheric absorption in comparison to sub-GHz systems. In comparison to optical technology, the radar technique majorly benefits with respect to the penetration property such as cloud/smoke cover penetration and detection of concealed objects. However, the THz range and synthetic aperture radar (SAR) imaging of concealed objects are not very well established. Therefore, this paper examines this property at THz. A testbed has been set up with a bandwidth of 110 GHz at a carrier frequency of 275 GHz. The imaging is performed of a very small metal object. Firstly, the sub-mm resolution is validated with the experiment after that the range and SAR imaging are performed in which this object is covered with different types of materials. The backscattered data is processed with the image reconstruction algorithms and the results are presented in this paper with respect to sub-mm resolution and detection. © 2020 IEEE.
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| 14. |
- Björklund, Svante, et al.
(författare)
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Factors Affecting the Effective Clutter Rank for Planar and Conformal Antennas with Subarrays
- 2023
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Ingår i: Proceedings of the IEEE Radar Conference 2023. - : Institute of Electrical and Electronics Engineers (IEEE).
-
Konferensbidrag (refereegranskat)abstract
- The Effective Clutter Rank (ECR), the number of eigenvalues of the clutter covariance matrix larger than the white noise, has important consequences for the radar system when suppressing clutter with Space-Time Adaptive Processing (STAP), in terms of cost, complexity, usability and performance. In this paper some factors affecting the ECR are studied by simulations. The result is partly explained by theory from the literature. The main results are: 1) Factors affecting the ECR [subarray beam pointing direction, subarray design, antenna geometry, # radar pulses, PRF, radar velocity and target range]. 2) Differences between planar and conformal antennas. 3) A simulation-based rank calculation method for antennas with subarrays.
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| 15. |
- Campos, Alexandre B., et al.
(författare)
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Adaptive Target Enhancer : Bridging the Gap between Synthetic and Measured SAR Images for Automatic Target Recognition
- 2023
-
Ingår i: Proceedings of the IEEE Radar Conference. - : Institute of Electrical and Electronics Engineers (IEEE). - 9781665436694
-
Konferensbidrag (refereegranskat)abstract
- Automatic target recognition (ATR) algorithms have been successfully used for vehicle classification in synthetic aperture radar (SAR) images over the past few decades. For this application, however, the scarcity of labeled data is often a limiting factor for supervised approaches. While the advent of computer-simulated images may result in additional data for ATR, there is still a substantial gap between synthetic and measured images. In this paper, we propose the so-called adaptive target enhancer (ATE), a tool designed to automatically delimit and weight the region of an image that contains or is affected by the presence of a target. Results for the publicly released Synthetic and Measured Paired and Labeled Experiment (SAMPLE) dataset show that, by defining regions of interest and suppressing the background, we can increase the classification accuracy from 68% to 84% while only using artificially generated images for training. © 2023 IEEE.
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| 16. |
- Campos, Alexandre Becker, 1997-, et al.
(författare)
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False Alarm Reduction in Wavelength-Resolution SAR Change Detection Schemes by Using a Convolutional Neural Network
- 2022
-
Ingår i: IEEE Geoscience and Remote Sensing Letters. - : Institute of Electrical and Electronics Engineers Inc.. - 1545-598X .- 1558-0571. ; 19
-
Tidskriftsartikel (refereegranskat)abstract
- In this letter, we propose a method to reduce the number of false alarms in a wavelength-resolution synthetic aperture radar (SAR) change detection scheme by using a convolutional neural network (CNN). The detection is performed in two steps: change analysis and object classification. A simple technique for wavelength-resolution SAR change detection is implemented to extract potential targets from the image of interest. A CNN is then used for classifying the change map detections as either a target or nontarget, further reducing the false alarm rate (FAR). The scheme is tested for the CARABAS-II data set, where only three false alarms over a testing area of 96 km² are reported while still sustaining a probability of detection above 96%. We also show that the network can still reduce the FAR even when the flight heading of the SAR system measurement campaign differs by up to 100° between the images used for training and test. CCBY
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| 17. |
- Campos, Alexandre Becker, 1997-, et al.
(författare)
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UNSUPERVISED AUTOMATIC TARGET DETECTION FOR MULTITEMPORAL SAR IMAGES BASED ON ADAPTIVE K-MEANS ALGORITHM
- 2020
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Konferensbidrag (refereegranskat)abstract
- In this paper, we present an unsupervised automatic target detection algorithm for multitemporal SAR images. The proposed two-fold method is expected to reduce processing time for large scene sizes with sparse targets while still improving detection performance. Firstly, pixel blocks are extracted from an initial change map to reduce the algorithm's search space and favor target detection. Secondly, an adaptive k-means algorithm selects the number of clusters that better separates targets from false alarms, which are discarded. Preliminary results show the advantages of the proposed method in processing time and detection performance over a recently proposed supervised method for the CARABAS-II dataset.
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| 18. |
- da Silva, Fabiano G., et al.
(författare)
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Hybrid Feature Extraction Based on PCA and CNN for Oil Rig Classification in C-Band SAR Imagery
- 2022
-
Ingår i: Proceedings of SPIE - The International Society for Optical Engineering. - : SPIE - International Society for Optical Engineering.
-
Konferensbidrag (refereegranskat)abstract
- Feature extraction techniques play an essential role in classifying and recognizing targets in synthetic aperture radar (SAR) images. This article proposes a hybrid feature extraction technique based on convolutional neural networks and principal component analysis. The proposed method is used to extract features of oil rigs and ships in C-band synthetic aperture radar polarimetric images obtained with the Sentinel-1 satellite system. The extracted features are used as input in the logistic regression (LR), support vector machine (SVM), random forest (RF), naive Bayes (NB), decision tree (DT), and k-nearest-neighbors (kNN) classification algorithms. Furthermore, the statistical tests of Kruskal-Wallis and Dunn were considered to show that the proposed extraction algorithm has a significant impact on the performance of the classifiers. © 2022 SPIE.
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| 19. |
- Dahl, Mattias, et al.
(författare)
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Verifiering av mätmetoder, Yttäckande mätningar med SAR
- 2017
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Inom ARENA, den svenska kunskapsplattformen för vägavgifter,har vi tidigare föreslagit satellitbase-rad Syntetisk Apertur Radar (SAR) för att göra effektutvärderingsmätningar av lastbilstrafik över stora områden av Sverige. Denna nya mätmetod är mycket lovande och syftet med detta delprojekt har varit att studera hur ett urval avmätområden kan ske om man avser att genomföra trafikmätningar ur ett effektutvärderingsperspektiv. Som utgångspunkt för rapporten används resultatetfrån de mätningar som inom ramen för ARENA tidigarehar genomförts och avrapporterats, det vill sägaenserie avmätning över södra Sverige där satellitsystemetTerraSAR-X användes för att mäta trafik. Motiveringen till att använda ett satellitsy-stemmed SAR är kostnadseffektivitetenoch förmåganatt mäta trafik på samma sättöver hela Sve-rige och dessutomunder allaåretsdagaroavsett väderlek. Beräkningarna för var man skall eller bör mäta baserar sig på underlag från Nationell vägdata-bas(NVDB) som ärTrafikverketsdatabas över vägnätet i Sverige. Detta underlagi form av trafikflö-denhar i sin tur fått utgöra ett underlag tillhur satellitmätningar kan skei olika landsändar det vill sägaförmågan att observeralastbilstrafiki de aktuella områdena.Avsikten med en mätning av detta slag är att den härledda informationen ska levereras till slutanvän-darevars syfte är att utvärdera effekterna av en Vägslitageskatt. Idenna rapport presenteras kartor ur vilka intressanta områden ur olika aspekter kan väljas ur och inte minst var man i sådant fall skall eller bör mäta.Rapporten avslutas med ett mer teoretiskt resonemang kring hur effektiva skatt-ningar av medeltrafikur ett satellitperspektiv skulle kunna betraktas ochi någon meninghur mät-ningar och den efterföljande statistiska databehandlingendärigenomblir så effektiv som möjligt.
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| 20. |
- Dahl, Mattias, et al.
(författare)
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Yttäckande mätningar med satellit - Studie avmätmetoder och datafångst
- 2017
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Avståndsbaserade vägavgiftssystem införs successivt i många länder världen över. Effekten av ett systems implementering kan i många delar vara svårt att analysera, inte minst ur ett mer övergri-pande perspektiv. Denna rapport är en studierörande en helt ny typ av satellitbaserad,yttäckande mätteknik som har genomförts inom ARENA, den svenska kunskapsplattformen för brukaravgifter i transportsektorn. Den yttäckande trafikmätningen sker med avancerad radarteknik som blivit tillgänglig under de sen-aste åren och där vi idag befinner oss i ett stort skifte på så sätt att tillgängligheten av data kommer att öka betydande de närmsta åren. Rapporten innehåller resultat från ett fältförsök över södra Sverige där det tyska satellitsystemet TerraSAR-X användes. Syftet är också att få en uppfattning över hur metodiken, som krävs vid en fullskalig satellitmätning, ser ut. Det vill säga hur man skall välja ut mätområdet, beställning av mät-ning över mätområdet, nedladdning av satellitdatauttag samt en verifiering av hur mätningarna på olika sätt kan bidra till före-och efteranalyser vid ett eventuellt införande av ett vägavgiftssystem.Rapporten har ett övergripande mål att knyta an till de inom ARENAidentifierade domäner, faktorer och nyckeltal som i sin tur ansetts vara relevanta för att utvärdera effekterna av ett införande av en vägslitageskatt för tung trafik. Rapportens huvudsakliga fokus är vad som möjligt att mäta från satel-litbaserade system men även i någon mening översiktligt uppskatta förmågan hos andra yttäckande system såsom drönare och flygburna system. Det vill säga vad systemen kan förväntas leverera uti-från en analys kring tillgänglighet, kvalitet, kostnad och användbarhet.
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| 21. |
-
En båge genom tiden - ritualer kring en göteborgshistoria. Om Flickläroverket i Artisten
- 2024
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Samlingsverk (redaktörskap) (övrigt vetenskapligt/konstnärligt)abstract
- 1929 bildades Göteborgs första Högre allmänna läroverk för Flickor – Flickläroverket som fick en byggnad 1935 i det kulturella centrumet, Götaplatsen. Efter några år som Kjellbergska gymnasiet, sedan Komvux, blev byggnaden del av Artisten, Högskolan för scen och musik, HSM 1992. Byggnaden har burit kvinnors utbildning, konst och kultur över många generationer, en minneskedja som nu är bruten. Boken - En båge genom tiden – ritualer kring en göteborgshistoria – en konst- och forskningsantologi – är resultatet av de offentliga minnesdagar där de deltagande drygt 200 kvinnorna (70– 97 år) som varit elever på Flickläroverket, studenter vid Artisten, konstnärer och forskare – bidrog till och deltog i gestaltande ritualer, minnesrum, dans, utställningar och samtal som gav liv åt en utbildningskultur och konst som berört samhället i generationer. I boken bidrar ett 20-tal Göteborgsbaserade konstnärer och forskare med olika perspektiv på byggnadens poetiska, sociala och konstnärliga dimensioner. Bland annat beskrivs återskapandet av Bågdansen, som dansades varje år vid Lucia mellan 1934-1972. Här beskrivs även den medie-debatt som ledde till räddningen av målningen Dansen av Nils Nilsson från 1935 och hur nedtagningen gick till. Tillsammans med ett rikt foto- och bildmaterial, filmdokumentationer och ett ljudarkiv utgör boken ett tidsdokument där konst fungerar som minnesbärare över tid och rum.
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| 22. |
- Fabrin, Ana, et al.
(författare)
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A CFAR optimization for low frequency UWB SAR change detection algorithms
- 2017
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Ingår i: International Geoscience and Remote Sensing Symposium (IGARSS). - : Institute of Electrical and Electronics Engineers Inc.. - 9781509049516 ; , s. 1071-1074
-
Konferensbidrag (refereegranskat)abstract
- This paper presents a study on the constant false alarm rate (CFAR) filter design for change detection algorithms (CDA). More specifically, we are interested in CFAR filters used in CDA for low frequency ultra-wideband (UWB) synthetic aperture radar (SAR) systems. The filter design performance was evaluated in terms of false alarm rate (FAR) and probability of detection (PD). For evaluation purposes, we considered a set of SAR images obtained with the CARABAS-II system. The results are compared with the ones presented in [1], where the same CDA was considered, except for the CFAR filter. The results show that relevant FAR performance improvements can be obtained by just modifying the CFAR filter parameters taking into account the image resolution and target characteristics. © 2017 IEEE.
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| 23. |
- Gomes, Natanael Rodrigues, et al.
(författare)
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Comparison of the Rayleigh and K-Distributions for Application in Incoherent Change Detection
- 2019
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Ingår i: IEEE Geoscience and Remote Sensing Letters. - : IEEE. - 1545-598X .- 1558-0571. ; 16, s. 756-760
-
Tidskriftsartikel (refereegranskat)abstract
- The aim of this letter is to compare two incoherent change-detection algorithms for target detection in low-frequency ultrawideband (UWB) synthetic aperture radar (SAR) images. The considered UWB SAR operates in the frequency range from 20 to 90 MHz. Both approaches employ a likelihood ratio test according to the Neyman–Pearson criterion. First, the bivariate Rayleigh probability distribution is used to implement the likelihood ratio test function. This distribution is well known and has been used for change-detection algorithms in low-frequency UWB SAR with good results. Aiming to minimize the false alarm rate and taking into consideration that low-frequency UWB SAR images have high resolution compared to the transmitted wavelength, the second approach implements the test by using a bivariate K-distribution. This distribution has scale and shape parameters that can be used to adjust it to the data. No filter is applied to the data set images, and the results show that with a good statistical model, it is not needed to rely on filtering the data to decrease the number of false alarms. Therefore, we can have a better tradeoff between resolution and detection performance.
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| 24. |
- Hallösta, Simon, 1994-, et al.
(författare)
-
Effects of Foreground Augmentations in Synthetic Training Data on the Use of UAVs for Weed Detection
- 2024
-
Ingår i: Proceedings of Machine Learning Research. - : ML Research Press.
-
Konferensbidrag (refereegranskat)abstract
- This study addresses the issue of black-grass, a herbicide-resistant weed that threatens wheat yields in Western Europe, through the use of high- resolution Unmanned Aerial Vehicles (UAVs) and synthetic data augmentation in precision agriculture. We mitigate challenges such as the need for large labeled datasets and environmental variability by employing synthetic data augmentations in training a Mask R-CNN model. Using a minimal dataset of 43 black-grass and 12 wheat field images, we achieved a 37% increase in Area Under the Curve (AUC) over the non-augmented baseline, with scaling as the most effective augmentation. The best model attained a recall of 53% at a precision of 64%, offering a promising approach for future precision agriculture applications. © NLDL 2024. All rights reserved.
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| 25. |
- Hallösta, Simon, 1994-, et al.
(författare)
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Impact of Neural Network Architecture for Fingerprint Recognition
- 2024
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Ingår i: Intelligent Systems and Pattern Recognition. - : Springer. - 9783031463341 - 9783031463358 ; , s. 3-14
-
Konferensbidrag (refereegranskat)abstract
- This work investigates the impact of the neural networks architecture when performing fingerprint recognition. Three networks are studied; a Triplet network and two Siamese networks. They are evaluated on datasets with specified amounts of relative translation between fingerprints. The results show that the Siamese model based on contrastive loss performed best in all evaluated metrics. Moreover, the results indicate that the network with a categorical scheme performed inferior to the other models, especially in recognizing images with high confidence. The Equal Error Rate (EER) of the best model ranged between 4%−11% which was on average 6.5 percentage points lower than the categorical schemed model. When increasing the translation between images, the networks were predominantly affected once the translation reached a fourth of the image. Our work concludes that architectures designed to cluster data have an advantage when designing an authentication system based on neural networks.
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| 26. |
- Hjälmdahl, Magnus, et al.
(författare)
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Effektutvärdering av kilometerskatt : Slutrapport. Slutsats och rekommendation
- 2017
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Urinsikten om behovet av brukaravgifter inom transportsektornföddes idén att skapa en arena för den samlade kompetenseni Sverige. Detta blev ARENA-projektet, vars första fas,2006-2008,hade som mål attutveckla ett koncept för ett vägavgiftssystem för lastbilar.Den andra fasen avslutades2011 med syftet att verifiera det utvecklade vägavgiftskonceptet genom praktiska demonstrationer. Projektet lade även grunden för en innovationsmiljö inom ITS, som är knuten till NetPort Science Park och Blekinge Tekniska Högskola.I den tredje fasen breddades anslaget till att stödja utveckl-ingen av samverkan och interoperabilitet mellan olika system för exempelvis trängselskatt, infra-strukturavgifter eller kilometerskatt, såväl i Sverige som internationellt.Från 2015 har ARENA övergått till att vara en långsiktig nationell kunskapsplattform för brukaravgif-ter inom transportsektorn. Inom ARENA drivs olika projekt beroende på de problemställningar som är aktuella i samhället. Ett av dessa handlar om att utveckla metodik för effektutvärdering av kilome-terskatt för tunga fordonDetta projekt har löpt parallellt med Vägslitageskattekommitténarbete och som ARENAsamverkat medoch stöttat.Arbetet inom ARENA fokuserarpå attutreda vilka effekterav en kilometerskatt som är troliga/möj-liga och vilka av dessa som i sin tur är möjliga att observeraoch hur de kan observeras. Detta har gjorts genom bl.a. inventeringar av andra liknande initiativ och hur de har utvärderats, litteraturge-nomgångar och workshops. Rapporter från detta arbete återfinns på projektets hemsida (http://www.arena-ruc.se/). Denna avslutande rapport fokuserar framförallt på övergripande slutsat-ser baserat på arbetet inom ARENA,samt de rekommendationer om datainsamling och utvärdering som projekt-och styrgruppen för ARENA anser är relevanta att nu gå vidare med, baserat på att ett beslut om införande av kilometerskatt inte har tagits och det är oklart huruvida beslut kommer att tas inom de närmaste åren. ARENA anser, med utgångspunkt i ovanstående, att en systematisk föremätning(ex-ante)bör ge-nomföras först när beslut om att införa skatten har tagits och det finns detaljerad information om hur skatten är utformad.ARENA anser dock att kunskapsnivån om godstransporter på väg generellt sett är bristfällig varför det är motiverat att inleda datafångst inom vissa utpekade områden för att stärka kunskapen. Den data som bör samlas in är värdefull också i samband med utvärdering av ef-fekterna av t.ex. förändrade cabotageregler, ändrade gränser för lastbilars mått och vikt, ändrad energi-och koldioxidbeskattning etc.Det pågår idag flera nationella initiativ kring förbättrat kunskapsunderlag om yrkestrafiken och gods-transporter på väg. ARENAs rekommendationer ligger i linje med dessa och arbetet kring att öka kun-skapsnivån bör fortgå.
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| 27. |
- Ivanenko, Yevhen, et al.
(författare)
-
Autofocusing of THz SAR Images by Integrating Compressed Sensing into the Backprojection Process
- 2023
-
Ingår i: Proceedings of the IEEE Radar Conference. - : Institute of Electrical and Electronics Engineers (IEEE). - 9781665436694
-
Konferensbidrag (refereegranskat)abstract
- The THz frequency spectrum provides an opportunity to explore high-resolution synthetic-aperture-radar (SAR) short-range imaging that can be used for various applications. However, the performance of THz SAR imaging is sensitive to phase errors that can be caused by an insufficient amount of data samples for image formation and by path deviations that can be practically caused by SAR platform vibrations, changes in speed, changes in direction, and acceleration. To solve the former problem, an improved interpolation procedure for backprojection algorithms has been proposed. However, to make these algorithms efficient in handling the latter problem, an additional autofocusing is necessary. In this paper, we introduce an autofocusing procedure based on compressed sensing that is incorporated into the backprojection algorithm. The reconstruction is based on the following calculated parameters: windowed interpolation sinc kernel, and range distances between SAR platform and image pixels in a defined image plane. The proposed approach is tested on real data, which was acquired by the 2\pi FMCW SAR system through outdoor SAR imaging. © 2023 IEEE.
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| 28. |
- Ivanenko, Yevhen, et al.
(författare)
-
Interpolation methods for SAR backprojection at THz frequencies
- 2021
-
Ingår i: 2021 4th International Workshop on Mobile Terahertz Systems, IWMTS 2021. - : Institute of Electrical and Electronics Engineers Inc.. - 9781728184395
-
Konferensbidrag (refereegranskat)abstract
- The paper proposes the extensions of the available linear and cubic interpolation methods for backprojecting complex SAR data into an image plane. Due to the fact that the phase of complex SAR data is very sensitive to the shift in time, the proposed interpolations include the phase control of the interpolated complex values. The proposed methods are examined with the global backprojection algorithm that is used to process SAR data at THz frequencies. In numerical examples, a two-dimensional indoor THz SAR imaging for a point target is considered, where the developed interpolation methods are compared with the nearest neighbor approach. © 2021 IEEE.
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| 29. |
- Ivanenko, Yevhen, et al.
(författare)
-
Interpolation Methods with Phase Control for Backprojection of Complex-Valued SAR Data†
- 2022
-
Ingår i: Sensors. - : MDPI. - 1424-8220. ; 22:13
-
Tidskriftsartikel (refereegranskat)abstract
- Time-domain backprojection algorithms are widely used in state-of-the-art synthetic aperture radar (SAR) imaging systems that are designed for applications where motion error compensation is required. These algorithms include an interpolation procedure, under which an unknown SAR range-compressed data parameter is estimated based on complex-valued SAR data samples and backprojected into a defined image plane. However, the phase of complex-valued SAR parameters estimated based on existing interpolators does not contain correct information about the range distance between the SAR imaging system and the given point of space in a defined image plane, which affects the quality of reconstructed SAR scenes. Thus, a phase-control procedure is required. This paper introduces extensions of existing linear, cubic, and sinc interpolation algorithms to interpolate complex-valued SAR data, where the phase of the interpolated SAR data value is controlled through the assigned a priori known range time that is needed for a signal to reach the given point of the defined image plane and return back. The efficiency of the extended algorithms is tested at the Nyquist rate on simulated and real data at THz frequencies and compared with existing algorithms. In comparison to the widely used nearest-neighbor interpolation algorithm, the proposed extended algorithms are beneficial from the lower computational complexity perspective, which is directly related to the offering of smaller memory requirements for SAR image reconstruction at THz frequencies. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
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| 30. |
- Ivanenko, Yevhen, et al.
(författare)
-
Phase Control in Interpolation for Backprojection of THz FMCW SAR Signals
- 2022
-
Ingår i: 2022 23rd International Radar Symposium (IRS). - : IEEE. - 9788395602054 ; , s. 10-15
-
Konferensbidrag (refereegranskat)abstract
- The THz frequency spectrum opens a lot of applications in the imaging at sub-mm level. The increase of the operating frequency band for SAR imaging systems to the THz range has proportionally affected the amount of raw data to be stored and used for accurate image reconstruction. As a consequence, improvements in the existing SAR imaging algorithms to reduce the amount of data needed to achieve the appropriate quality of imaging is desired. This paper introduces the phase control procedure as an extension to the existing sinc interpolator for backprojecting complex-valued FMCW SAR data into a defined image plane. The proposed extension controls the phase of interpolated complex-valued SAR data parameters so that it includes appropriate information about the range distance between the SAR system and the given point of space. The extended algorithm is incorporated into the global backprojection algorithm and examined on the measurement data acquired via the 2pSENSE FMCW SAR system. The efficiency of the extended algorithm is evaluated through the comparison with the conventional nearest neighbor and sinc interpolation algorithms. © 2022 Warsaw University of Technology.
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| 31. |
- Javadi, Mohammad Saleh, 1986-, et al.
(författare)
-
Adjustable Contrast Enhancement Using Fast Piecewise Linear Histogram Equalization
- 2020
-
Ingår i: PROCEEDINGS OF THE 2020 3RD INTERNATIONAL CONFERENCE ON IMAGE AND GRAPHICS PROCESSING (ICIGP 2020). - New York, NY, USA : Association for Computing Machinery. - 9781450377201 ; , s. 57-61
-
Konferensbidrag (refereegranskat)abstract
- Histogram equalization is a technique to enhance the contrast of the image by redistributing the histogram. In this paper, a fast piecewise linear histogram equalization method is introduced based on an adjustable degree of enhancement and piecewise continuous transformation functions using frequencies of different grey-levels. This method aims to address and maximize the contrast enhancement of the image by stretching the entire spectrum. For this purpose, particular nodes (bins) on the histogram are simultaneously detected that in comparison with recursive methods, it requires less computational time. Then, the particular nodes are stretched using transformation functions to align with the reference nodes. The experimental results indicate that the performance of the proposed method is promising in terms of contrast enhancement. Moreover, this method preserves the texture of various regions in the image very well through the equalization process by using the degree of enhancement. © 2020 Owner/Author.
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| 32. |
- Javadi, Mohammad Saleh, 1986-, et al.
(författare)
-
Change detection in aerial images using three-dimensional feature maps
- 2020
-
Ingår i: Remote Sensing. - : MDPI. - 2072-4292. ; 12:9
-
Tidskriftsartikel (refereegranskat)abstract
- Interest in aerial image analysis has increased owing to recent developments in and availabilityofaerialimagingtechnologies,likeunmannedaerialvehicles(UAVs),aswellasagrowing need for autonomous surveillance systems. Variant illumination, intensity noise, and different viewpointsareamongthemainchallengestoovercomeinordertodeterminechangesinaerialimages. In this paper, we present a robust method for change detection in aerial images. To accomplish this, the method extracts three-dimensional (3D) features for segmentation of objects above a defined reference surface at each instant. The acquired 3D feature maps, with two measurements, are then used to determine changes in a scene over time. In addition, the important parameters that affect measurement, such as the camera’s sampling rate, image resolution, the height of the drone, and the pixel’sheightinformation,areinvestigatedthroughamathematicalmodel. Toexhibititsapplicability, the proposed method has been evaluated on aerial images of various real-world locations and the results are promising. The performance indicates the robustness of the method in addressing the problems of conventional change detection methods, such as intensity differences and shadows.
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| 33. |
- Javadi, Mohammad Saleh, 1986-
(författare)
-
Computer Vision Algorithms for Intelligent Transportation Systems Applications
- 2018
-
Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- In recent years, Intelligent Transportation Systems (ITS) have emerged asan efficient way of enhancing traffic flow, safety and management. Thesegoals are realized by combining various technologies and analyzing the acquireddata from vehicles and roadways. Among all ITS technologies, computervision solutions have the advantages of high flexibility, easy maintenanceand high price-performance ratio that make them very popular fortransportation surveillance systems. However, computer vision solutionsare demanding and challenging due to computational complexity, reliability,efficiency and accuracy among other aspects. In this thesis, three transportation surveillance systems based on computervision are presented. These systems are able to interpret the imagedata and extract the information about the presence, speed and class ofvehicles, respectively. The image data in these proposed systems are acquiredusing Unmanned Aerial Vehicle (UAV) as a non-stationary sourceand roadside camera as a stationary source. The goal of these works is toenhance the general performance of accuracy and robustness of the systemswith variant illumination and traffic conditions. This is a compilation thesis in systems engineering consisting of threeparts. The red thread through each part is a transportation surveillancesystem. The first part presents a change detection system using aerial imagesof a cargo port. The extracted information shows how the space isutilized at various times aiming for further management and developmentof the port. The proposed solution can be used at different viewpoints andillumination levels e.g. at sunset. The method is able to transform the imagestaken from different viewpoints and match them together. Thereafter,it detects discrepancies between the images using a proposed adaptive localthreshold. In the second part, a video-based vehicle's speed estimationsystem is presented. The measured speeds are essential information for lawenforcement and they also provide an estimation of traffic flow at certainpoints on the road. The system employs several intrusion lines to extractthe movement pattern of each vehicle (non-equidistant sampling) as an inputfeature to the proposed analytical model. In addition, other parameters such as camera sampling rate and distances between intrusion lines are alsotaken into account to address the uncertainty in the measurements and toobtain the probability density function of the vehicle's speed. In the thirdpart, a vehicle classification system is provided to categorize vehicles into\private car", \light trailer", \lorry or bus" and \heavy trailer". This informationcan be used by authorities for surveillance and development ofthe roads. The proposed system consists of multiple fuzzy c-means clusterings using input features of length, width and speed of each vehicle. Thesystem has been constructed by using prior knowledge of traffic regulationsregarding each class of vehicle in order to enhance the classification performance.
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| 34. |
- Javadi, Mohammad Saleh, 1986-, et al.
(författare)
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Design of a video-based vehicle speed measurement system : an uncertainty approach
- 2018
-
Ingår i: <em>2018 Joint 7th International Conference on Informatics, Electronics & Vision (ICIEV) and 2018 2nd International Conference on Imaging, Vision & Pattern Recognition (icIVPR)</em>, Kitakyushu, Japan, 2018, pp. 44-49.. - : IEEE. - 9781538651612
-
Konferensbidrag (refereegranskat)abstract
- Speed measurement is one of the key components of intelligent transportation systems. It provides suitable information for traffic management and law enforcement. This paper presents a versatile and analytical model for a video-based speed measurement in form of the probability density function (PDF). In the proposed model, the main factors contributing to the uncertainties of the measurement are considered. Furthermore, a guideline is introduced in order to design a video-based speed measurement system based on the traffic and other requirements. As a proof of concept, the model has been simulated and tested for various speeds. An evaluation validates the strength of the model for accurate speed measurement under realistic circumstances.
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| 35. |
- Javadi, Mohammad Saleh, 1986-, et al.
(författare)
-
Vehicle classification based on multiple fuzzy c-means clustering using dimensions and speed features
- 2018
-
Ingår i: Procedia Computer Science. - : Elsevier. ; , s. 1344-1350
-
Konferensbidrag (refereegranskat)abstract
- Vehicle classification has a significant use in traffic surveillance and management. There are many methods proposed to accomplish this task using variety of sensorS. In this paper, a method based on fuzzy c-means (FCM) clustering is introduced that uses dimensions and speed features of each vehicle. This method exploits the distinction in dimensions features and traffic regulations for each class of vehicles by using multiple FCM clusterings and initializing the partition matrices of the respective classifierS. The experimental results demonstrate that the proposed approach is successful in clustering vehicles from different classes with similar appearanceS. In addition, it is fast and efficient for big data analysiS.
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| 36. |
- Javadi, Mohammad Saleh, 1986-, et al.
(författare)
-
Vehicle speed measurement model for video-based systems
- 2019
-
Ingår i: Computers & electrical engineering. - : Elsevier. - 0045-7906 .- 1879-0755. ; 76, s. 238-248
-
Tidskriftsartikel (refereegranskat)abstract
- Advanced analysis of road traffic data is an essential component of today's intelligent transportation systems. This paper presents a video-based vehicle speed measurement system based on a proposed mathematical model using a movement pattern vector as an input variable. The system uses the intrusion line technique to measure the movement pattern vector with low computational complexity. Further, the mathematical model introduced to generate the pdf (probability density function) of a vehicle's speed that improves the speed estimate. As a result, the presented model provides a reliable framework with which to optically measure the speeds of passing vehicles with high accuracy. As a proof of concept, the proposed method was tested on a busy highway under realistic circumstances. The results were validated by a GPS (Global Positioning System)-equipped car and the traffic regulations at the measurement site. The experimental results are promising, with an average error of 1.77 % in challenging scenarios.
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| 37. |
- Javadi, Saleh, 1986-, et al.
(författare)
-
Harbour Area Change Detection and Analysis Using SAR Images from a Recent Measurement Campaign
- 2023
-
Ingår i: Proceedings of the IEEE Radar Conference 2023. - : Institute of Electrical and Electronics Engineers (IEEE).
-
Konferensbidrag (refereegranskat)abstract
- Synthetic aperture radar (SAR) data are widely used for remote sensing applications, such as change detection and environmental monitoring. This paper presents a recent measurement campaign for SAR images using the LORA system and investigates the applicability of the collected data for change detection. The region of interest in this study is a busy commercial harbour area in the south of Sweden. During the measurements, there were significant changes on the ground in the parking lot as trucks were disembarking a ship. The obtained SAR images were first filtered to have similar regions of interest in the Fourier domain to increase the coherence magnitude. Then, a constant false alarm rate (CFAR) algorithm was employed to detect changes with respect to trucks. In addition, optical aerial images were collected during this measurement campaign and were utilized to adjust the CFAR detection threshold. As a result, all the changed and unchanged regions corresponding to the selected targets were detected successfully. Moreover, a pattern of trucks’ utilization of the harbour’s parking lot during this peak time was obtained. The results demonstrate the applicability of the data from the ongoing measurement campaign and the possibility of further algorithm development for target detection and classification.
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| 38. |
- Javadi, Saleh, 1986-, et al.
(författare)
-
Performance Evaluation of Unsupervised Coregistration Algorithms for Multitemporal SAR Images
- 2022
-
Ingår i: International Geoscience and Remote Sensing Symposium (IGARSS). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781665427920 ; , s. 64-67
-
Konferensbidrag (refereegranskat)abstract
- In this paper, we present three algorithms for the multitemporal synthetic aperture radar (SAR) images coregistration. The proposed algorithms are a 2-D cross correlation, a 1-D parabolic based, and a 2-D projective transformation. The 2-D cross correlation algorithm is used to obtain coarse estimation of the displacement for coregistration. In the second method, two independent 1-D parabolic interpolations are calculated to refine the estimation of the peak location of the cross correlation matrix with subpixel accuracy. Finally, in the third method, a 2-D projective transformation is employed to align the SAR images using point correspondences and the cubic interpolation. The performance evaluation of these algorithms are provided based on the coherence magnitude and the absolute displacement error for a point target using a corner reflector in the scene. The experimental results obtained on real recorded multitemporal satellite SAR data demonstrate the effectiveness and the computational complexity of these algorithms. © 2022 IEEE.
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| 39. |
- Javadi, Saleh, 1986-, et al.
(författare)
-
Vehicle Detection in Aerial Images Based on 3D Depth Maps and Deep Neural Networks
- 2021
-
Ingår i: IEEE Access. - : Institute of Electrical and Electronics Engineers (IEEE). - 2169-3536. ; 9, s. 8381-8391
-
Tidskriftsartikel (refereegranskat)abstract
- Object detection in aerial images, particularly of vehicles, is highly important in remote sensing applications including traffic management, urban planning, parking space utilization, surveillance, and search and rescue. In this paper, we investigate the ability of three-dimensional (3D) feature maps to improve the performance of deep neural network (DNN) for vehicle detection. First, we propose a DNN based on YOLOv3 with various base networks, including DarkNet-53, SqueezeNet, MobileNet-v2, and DenseNet-201. We assessed the base networks and their performance in combination with YOLOv3 on efficiency, processing time, and the memory that each architecture required. In the second part, 3D depth maps were generated using pairs of aerial images and their parallax displacement. Next, a fully connected neural network (fcNN) was trained on 3D feature maps of trucks, semi-trailers and trailers. A cascade of these networks was then proposed to detect vehicles in aerial images. Upon the DNN detecting a region, coordinates and confidence levels were used to extract the corresponding 3D features. The fcNN used 3D features as the input to improve the DNN performance. The data set used in this work was acquired from numerous flights of an unmanned aerial vehicle (UAV) across two industrial harbors over two years. The experimental results show that 3D features improved the precision of DNNs from 88.23 % to 96.43 % and from 97.10 % to 100 % when using DNN confidence thresholds of 0.01 and 0.05, respectively. Accordingly, the proposed system was able to successfully remove 72.22 % to 100 % of false positives from the DNN outputs. These results indicate the importance of 3D features utilization to improve object detection in aerial images for future research. CCBY
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| 40. |
- Ludwig Barbosa, Vinícius, 1990-, et al.
(författare)
-
A Simulation Study of the Effect of Ionospheric Vertical Gradients on the Neutral Bending Angle Error for GNSS Radio Occultation
- 2017
-
Ingår i: Progress in Electromagnetics Research Symposium. - : IEEE. - 9781538612118 ; , s. 1540-1545
-
Konferensbidrag (refereegranskat)abstract
- Radio Occultation based on Global Navigation Satellite System signals (GNSS RO) is an increasingly important remote sensing technique. Its measurements are used to derive parameter of the Earth's atmosphere, e.g., pressure, temperature and humidity, with good accuracy. The systematic residual error present on the data processing is related to ionospheric conditions, such as the distribution of electrons and the resultant vertical gradient. This study investigates the relationship between these parameters and the residual ionospheric error (RIE) on the retrieved bending angle in the stratosphere. Chapman function combined to sinusoidal perturbations are used to model electron density profiles and compared to RO retrievals of the ionosphere to perform the investigation. The results confirmed that the major ionospheric influence on the retrieval error is related to the F-layer electron density peak, whereas small-scale vertical structures play a minor role.
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| 41. |
- Ludwig Barbosa, Vinícius, 1990-, et al.
(författare)
-
Detection and localization of F-layer ionospheric irregularities with the back-propagation method along the radio occultation ray path
- 2023
-
Ingår i: Atmospheric Measurement Techniques. - : Copernicus Publications. - 1867-1381 .- 1867-8548. ; 16:7, s. 1849-1864
-
Tidskriftsartikel (refereegranskat)abstract
- The back propagation (BP) method consists of diffractive integrals computed over a trajectory path, projecting a signal to different planes. It unwinds the diffraction and multipath, resulting in minimum disturbance on the BP amplitude when the auxiliary plane coincides with the region causing the diffraction. The method has been previously applied in GNSS Radio Occultation (RO) measurements showing promising results in the location estimate of ionospheric irregularities but without complementary data to validate the estimation. In this study, we investigate with wave optics propagator (WOP) simulations of an equatorial C/NOFS occultation with scintillation signatures caused by an equatorial plasma bubble (EPB), which was parametrized with aid of collocated data. In addition, a few more test cases were designed to assess the BP method regarding size, intensity and placement of single and multiple irregularity regions. The results show a location estimate accuracy of 10 km (single bubble, reference case), where in multiple bubble scenarios only the strongest disturbance would be resolved properly. The minimum detectable disturbance level and the estimation accuracy depend on the receiver noise level, and in the case of several bubbles on the distance between them. The remarks of the evaluation supported the interpretation of results for two COSMIC occultations.
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| 42. |
- Ludwig Barbosa, Vinícius, 1990-
(författare)
-
Effects of Small-Scale Ionospheric Irregularities on GNSS Radio Occultation Signals : Evaluations Using Multiple Phase Screen Simulator
- 2019
-
Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Radio Occultation (RO) is a remote sensing technique which uses Global Navigation Satellite System (GNSS) signals tracked by a Low-Earth Orbit (LEO) satellite to sound the earth's atmosphere both in low (troposphere, stratosphere) and high (ionosphere) altitudes. GNSS-RO provides global coverage and SI traceable measurements of atmospheric data with high-vertical resolution. Refractivity, dry temperature, pressure and water vapour profiles retrieved from RO measurements have a relevant contribution in Numerical Weather Prediction (NWP) systems and in climate-monitoring.Due to the partial propagation through the ionosphere, a systematic bias is added to the lower atmospheric data product. Most of this contribution is removed by a linear combination of data for two frequencies. In climatology studies, one can apply a second-order correction - so called κ-correction - which relies on a priori information on the conditions in the ionosphere. However, both approaches do not remove high-order terms in the error due to horizontal gradient and earth's geomagnetic fields. The remaining residual ionospheric error (RIE) and its systematic bias in RO atmospheric data is a well-known issue and its mitigation is an open research topic.In this licentiate dissertation, the residual ionospheric error after the standard correction is evaluated with computational simulations using a wave optics propagator (WOP). Multiple Phase Screen (MPS) method is used to simulate occultation events in different ionospheric scenarios, e.g. quiet and disturbed conditions. Electron density profiles (EDP) assumed in simulations are either defined by analytical equations or measurements. The disturbed cases are modelled as small-scale irregularities within F-region in two different ways: as sinusoidal fluctuations; and by using a more complex approach, where the irregularities follow a single-slope power-law that yields moderate to strong scintillation in the signal amplitude. Possible errors in MPS simulations assuming long segment of orbit and ionosphere are also evaluated.The results obtained with the sinusoidal disturbances show minor influence in the RIE after the standard correction, with the major part of the error due to the F-region peak. The implementation of the single-slope power-law is validated and the fluctuations obtained in simulation show good agreement to the ones observed in RO measurements. Finally, an alternative to overcome limitations in MPS simulations considering occultations with long segment of orbit and ionosphere is introduced and validated.The small-scale irregularities modelled in F-region with the power-law can be added in simulations of a large dataset subjected to κ-correction, in order to evaluate the RIE bending angle and the consequences in atmospheric parameters, e.g. temperature.
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| 43. |
- Ludwig Barbosa, Vinícius, 1990-, et al.
(författare)
-
Evaluation of Ionospheric Scintillation in GNSS Radio Occultation Measurements and Simulations
- 2020
-
Ingår i: Radio Science. - : Wiley-Blackwell Publishing Inc.. - 0048-6604 .- 1944-799X. ; 55:8
-
Tidskriftsartikel (refereegranskat)abstract
- Like any other system relying on trans-ionospheric propagation, GNSS Radio Occultation (GNSS-RO) is affected by ionospheric conditions during measurements. Regions of plasma irregularities in F-region create abrupt gradients in the distribution of ionized particles. Radio signals propagated through such regions suffer from constructive and destructive contributions in phase and amplitude, known as scintillations. Different approaches have been proposed in order to model and reproduce the wave propagation through ionospheric irregularities. We present simulations considering an one-component inverse power-law model of irregularities integrated with Multiple Phase Screen (MPS) propagation. In this work, the capability of the scintillation model to reproduce features in the signal amplitude of low latitude MetOp measurements in the early hours of DOY 76, 2015 (St. Patrick’s Day geomagnetic storm) is evaluated. Power spectral density (PSD) analysis, scintillation index, decorrelation time and standard deviation of neutral bending angle are considered in the comparison between the simulations and RO measurements. The results validate the capability of the simulator to replicate an equivalent total integrated phase variance in cases of moderate to strong scintillation.
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| 44. |
- Ludwig Barbosa, Vinícius, 1990-, et al.
(författare)
-
GNSS Radio Occultation Simulation Using Multiple Phase Screen Orbit Sampling
- 2020
-
Ingår i: IEEE Geoscience and Remote Sensing Letters. - : Institute of Electrical and Electronics Engineers (IEEE). - 1545-598X .- 1558-0571. ; 17:8, s. 1323-1327
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Tidskriftsartikel (refereegranskat)abstract
- Wave optics propagators (WOPs) are commonlyused to describe the propagation of radio signals through earth’satmosphere. In radio occultation (RO) context, multiple phasescreen (MPS) method has been used to model the effects of theatmosphere in Global Navigation Satellite System (GNSS) signalsduring an occultation event. WOP implementation includes,in addition to MPS, a diffraction integral as the final step tocalculate the radio signal measured in the low-earth orbit (LEO)satellite. This approach considers vacuum as the propagationmedium at high altitudes, which is not always the case when theionosphere is taken into account in simulations. An alternativeapproach is using MPS all the way to LEO in order to samplethe GNSS signal in orbit. This approach, named MPS orbitsampling (MPS-OS), is evaluated in this letter. Different scenariosof setting occultation assuming a short segment of the LEO orbithave been simulated using MPS and MPS-OS. Results have beencompared to Abel transform references. Furthermore, a longsegment scenario has been evaluated as well. A comparison ofbending angle (BA) and residual ionospheric error (RIE) showsthe equivalence between MPS and MPS-OS results. The mainapplication of MPS-OS should be in occultation events with longsegments of orbit and including ionosphere, in which a standardWOP may not be appropriate.
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| 45. |
- Ludwig Barbosa, Vinícius, 1990-, et al.
(författare)
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Location of Ionospheric Irregularities in Extended GNSS-RO Measurements Using Back Propagation Method
- 2023
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Ingår i: 2023 35th General Assembly and Scientific Symposium of the International Union of Radio Science, URSI GASS 2023. - : Institute of Electrical and Electronics Engineers (IEEE). - 9789463968096
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Konferensbidrag (refereegranskat)abstract
- Besides providing electron density profiles (EDP), GNSS Radio Occultation (GNSS-RO) measurements allow monitoring the frequency and the areas where ionospheric scintillations occur. In this work, RO measurements composing an experimental data set are processed with the back propagation (BP) method to estimate the location of sporadic E-clouds and equatorial plasma bubbles (EPB). The data set includes non-conventional measurements tracked up to 600 km (generally around 80 km), covering F-region heights, shortly before MetOp-A was decommissioned. Results indicate the combination of extended occultations and the BP method is promising for monitoring the occurrence and characterizing ionospheric irregularities in the F-region and the E-region. © 2023 International Union of Radio Science.
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| 46. |
- Ludwig Barbosa, Vinícius, 1990-
(författare)
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On the Ionospheric Influence on GNSS Radio Occultation Signals : Modelling and Assessment
- 2022
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Radio Occultation (RO) is a well-established remote sensing technique that uses Global Navigation Satellite System (GNSS) signals to sound the Earth’s atmosphere. GNSS-RO measurements provide high-resolution, vertical profiles of physical parameters from the lower atmosphere (troposphere and stratosphere), e.g., refractivity, dry temperature, pressure, and water vapour, with primary application in weather forecasting and climatology models. The upper atmosphere (ionosphere) is also sounded during measurements, in which information about total electron content, electron density profiles, and scintillation indices compose the RO ionospheric data product.The ionosphere is a dispersive medium composed of ionized particles. It is extensively conditioned by Solar activity and shows seasonal, geographical, and day- and night-time variation. Despite the benefit of the upper atmospheric data, the ionosphere influences the retrievals in the lower atmosphere by (i) adding an inherent systematic bias in bending angles, i.e., residual ionospheric error (RIE), and (ii) disturbing the signal amplitude and phase, i.e., scintillation, in the presence of irregularities regions on the electron density along the ray path, e.g., equatorial plasma bubbles. In this dissertation, both aspects are investigated by modelling the equatorial ionosphere, and its small-scale irregularities in simulations of occultation events to (i) reproduce the effects observed in measurements and (ii) assess methods that can extract information about the ionosphere and support its monitoring and modelling.The multiple phase screen method was applied to model the GNSS signal propagation through quiet and disturbed ionospheric conditions. The small-scale irregularities in the F-region were modelled by a single slope power law to yield moderate to strong scintillation in the signals. Results were assessed according to the amplitude and phase scintillation indices, RIE, the standard deviation of the retrieved bending angles, and power spectral density (PSD). A subset of these parameters was taken as features to train a classifier based on the support vector machine algorithm. The purpose of this model was to detect RO measurements affected by ionospheric scintillation. Specifically, those in which PSD could provide further information about the irregularities according to the scintillation theory. Additionally, the back propagation (BP) method and its capability to estimate the mean distance between the receiver and irregularities were evaluated.Applying spectral analysis techniques to RO measurements may contribute to the characterization of small-scale irregularities in equatorial plasma bubbles. The results from simulations applying the single-slope power law to model the irregularities showed a good agreement with the selected cases. The automatic detection of occultations affected by ionospheric irregularities has achieved similar performance to models trained with ground-based measurements. Furthermore, the BP method can add the estimation of the mean location to the spectral analysis information. Such tools can enlarge the amount of ionospheric data retrieved -- especially for occultations with extended vertical range and when combined with other sounding techniques.
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| 47. |
- Ludwig Barbosa, Vinícius, 1990-, et al.
(författare)
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Supervised Detection of Ionospheric Scintillation in Low-Latitude Radio Occultation Measurements
- 2021
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Ingår i: Remote Sensing. - : MDPI. - 2072-4292. ; 13:9
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Tidskriftsartikel (refereegranskat)abstract
- Global Navigation Satellite System (GNSS) Radio Occultation (RO) has provided high- quality atmospheric data assimilated in Numerical Weather Prediction (NWP) models and climatol- ogy studies for more than 20 years. In the satellite–satellite GNSS-RO geometry, the measurements are susceptible to ionospheric scintillation depending on the solar and geomagnetic activity, seasons, geographical location and local time. This study investigates the application of the Support Vector Machine (SVM) algorithm in developing an automatic detection model of F-layer scintillation in GNSS-RO measurements using power spectral density (PSD). The model is intended for future analyses on the influence of space weather and solar activity on RO data products over long time periods. A novel data set of occultations is used to train the SVM algorithm. The data set is composed of events at low latitudes on 15–20 March 2015 (St. Patrick’s Day geomagnetic storm, high solar flux) and 14–19 May 2018 (quiet period, low solar flux). A few conditional criteria were first applied to a total of 5340 occultations to define a set of 858 scintillation candidates. Models were trained with scintillation indices and PSDs as training features and were either linear or Gaussian kernel. The investigations also show that besides the intensity PSD, the (excess) phase PSD has a positive contribution in increasing the detection of true positives.
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| 48. |
- Mbiydzenyuy, Gideon, et al.
(författare)
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Effektutvärdering avkilometerskatt för tunga fordon : en omvärldsstudie
- 2016
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Over the last 15 years, distance-based road user charging schemes have been designed and deployed across the European Union. At least 10 EU countries today calculate, charge and collect fares for the use of road infrastructure following a differential model supported by positioning, communication, and other related technologies such as ANPR. As future road charging schemes are being developed, existing systems, although aimed at varying goals, will play a critical role in passing along their experiences to positively influence the development of future road charging schemes. This report set a high ambition to study the evaluation landscape in the domain of distance-based road user charging. Given the current efforts within the ARENA knowledge platform targeted toward the development of an evaluation methodology for a possible distance-based road user charging scheme in Sweden, the report was aimed at laying a solid foundation to ensure that the development of the methodology should as much as possible build on real world experiences. To that effect, 15 systems are identified and analysed, including two congestion-charging schemes (Gothenburg and Stockholm) and 13 distance-based charging schemes in Europe andother parts of the world. The predominantly literature review-based analysis aim to isolate the goals behind these different schemes, if and how the scheme was evaluated, including the questions that were raised in the evaluation, evaluation phases that were covered, the methods that were employed in collecting evaluation data, and analysing the data for possible effects. More important, the analysis aimed at understanding what proven effects were uncovered, as well as the lessons learned from the evaluation process. In order to perform an analysis, the above goals were disaggregated into concrete questions, e.g., for each specific system, what was the evaluation method employed. Secondary data was then collected mainly through Internet search within transport relevant databases. A number of criteria were consistently applied in filtering the secondary data sources, e.g., source quality. The analysis focused on determining if each evaluation report had a clear evaluation goal, motivation for choices of methods, based on real or synthetic data, and if there were clearly demonstrated effects that can be considered to be significant.The work in this study turned out to expose an unfortunate serious deficiency in evaluation material from existing distance-basedroad user charging schemes both from an ex-ante, and even more-so, from an ex-post perspective. Of the 15 systems identified (with the exception of the Gothenburg and Stockholm cases), only six had any material on evaluation, with half addressing an overall system perspective and the rest addressing some aspects of the system. Moreover, only one report actually conducted and related both ex-ante and ex-post perspectives (Switzerland) while most studies were limited to ex-ante.Overall, the analysis suggests that fiscal and environmental measures predominates the goal behind several distance-based road user charging schemes while traffic management and modal shift are on the opposite end. Results from evaluation of congestion schemes in Stockholm and Gothenburg, suggests significant reductions were observed in the overall traffic volume, although disproportionately between passenger cars and heavy vehicles. Results from distance-based road user charging schemes discussed in this report suggests the increasein transport costs to be consistent across different schemes, e.g., 5% to 7% in Germany. 4While this may be a fact, it is difficult to separate how much of it may be a result of speculation that in turn drives up prices and cost compared to real costs as aresult of the scheme. This is because distance-based charging schemes also benefits for transport organizations where they are implemented, e.g., when schemes provide subsidies for environmentally clean fleet such as in Germany and the Czech Republic, or when competition with foreign vehicles is normalized or when traffic adjustments results in reduced travel times as in Stockholm. Therefore, without hard facts it can be difficult to fully explain the net increase in transport costs as a consequence of distance-based road user charging.Expectations based on existing work are that as transport cost increases, so too will the shares in rail traffic and the income for infrastructure financing. Also, traffic volumes, empty runs, vehicle-km, and emissions, all turn to decrease due to the implementation of a distance-based road charging scheme. Schemes that account for the Euro class differentiations are seen to significantly alter that fleet demographics but no clear trends were reported. Most of the evaluation reports analysed lacked documentation on evaluation data which made it difficult to ascertain the quality of established impacts. This is not just a cost issue but also exposes a limitation in the entire evaluation methodology framework employed.A centralchallenge in conducting impact evaluation is to isolate specific effects within a system that can be associated specifically to distance-based road user charging. This is because such effects are often the results of several interdependent elements with versatile and far-reaching consequences all changing during the evaluation period. Based on the information analysed in this study, it can be recommended to consider as many indicators as possible when addressing impact evaluation for distance-based road user charging in Sweden. Such indicators should then provide a basis for collecting statistically representative data that span across several domains. We believe that it is better to have data about several indicators, even though such indicators may overlap, compared to having data about few indicators. A true representative sample should identify geographic areas of interest, vehicle categories of interest, as well as specific industries such as the forest industry. The sample should also cover a longer time period to emphasize the time variability of the data. The impacts and benefits of distance-based road user charging in Sweden can be amplified if; the control system design, ex-ante evaluation, and ex-post evaluation are all addressed simultaneously as these elements can significantly affect each other.
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| 49. |
- Mittmann Voigt, Gustavo Henrique, et al.
(författare)
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A Statistical Analysis for Intensity Wavelength-Resolution SAR Difference Images
- 2023
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Ingår i: Remote Sensing. - : MDPI. - 2072-4292. ; 15:9
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents a statistical analysis of intensity wavelength-resolution synthetic aperture radar (SAR) difference images. In this analysis, Anderson Darling goodness-of-fit tests are performed, considering two different statistical distributions as candidates for modeling the clutter-plus-noise, i.e., the background statistics. The results show that the Gamma distribution is a good fit for the background of the tested SAR images, especially when compared with the Exponential distribution. Based on the results of this statistical analysis, a change detection application for the detection of concealed targets is presented. The adequate selection of the background distribution allows for the evaluated change detection method to achieve a better performance in terms of probability of detection and false alarm rate, even when compared with competitive performance change detection methods in the literature. For instance, in an experimental evaluation considering a data set obtained by the Coherent All Radio Band Sensing (CARABAS) II UWB SAR system, the evaluated change detection method reached a detection probability of 0.981 for a false alarm rate of 1/km2. © 2023 by the authors.
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| 50. |
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