| 1. |
- 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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| 2. |
- 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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| 3. |
- 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
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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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| 4. |
- 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.
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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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| 5. |
- 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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| 6. |
- 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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| 7. |
- 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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| 8. |
- 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
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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
- 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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| 9. |
- 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
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Ingår i: IEEE Geoscience and Remote Sensing Letters. - : Institute of Electrical and Electronics Engineers Inc.. - 1545-598X .- 1558-0571. ; 19
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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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| 10. |
- 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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