| 1. |
- Alves, Dimas I., et al.
(author)
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Neyman-Pearson Criterion-Based Change Detection Methods for Wavelength-Resolution SAR Image Stacks
- 2022
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In: IEEE Geoscience and Remote Sensing Letters. - : Institute of Electrical and Electronics Engineers Inc.. - 1545-598X .- 1558-0571. ; 19
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Journal article (peer-reviewed)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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| 2. |
- Campos, Alexandre Becker, 1997-, et al.
(author)
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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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In: IEEE Geoscience and Remote Sensing Letters. - : Institute of Electrical and Electronics Engineers Inc.. - 1545-598X .- 1558-0571. ; 19
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Journal article (peer-reviewed)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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| 3. |
- Ivanenko, Yevhen, et al.
(author)
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Interpolation Methods with Phase Control for Backprojection of Complex-Valued SAR Data†
- 2022
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In: Sensors. - : MDPI. - 1424-8220. ; 22:13
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Journal article (peer-reviewed)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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| 4. |
- Ivanenko, Yevhen, et al.
(author)
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Phase Control in Interpolation for Backprojection of THz FMCW SAR Signals
- 2022
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In: 2022 23rd International Radar Symposium (IRS). - : IEEE. - 9788395602054 ; , s. 10-15
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Conference paper (peer-reviewed)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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| 5. |
- Javadi, Saleh, 1986-, et al.
(author)
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Performance Evaluation of Unsupervised Coregistration Algorithms for Multitemporal SAR Images
- 2022
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In: International Geoscience and Remote Sensing Symposium (IGARSS). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781665427920 ; , s. 64-67
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Conference paper (peer-reviewed)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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| 6. |
- Ludwig Barbosa, Vinícius, 1990-
(author)
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On the Ionospheric Influence on GNSS Radio Occultation Signals : Modelling and Assessment
- 2022
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Doctoral thesis (other academic/artistic)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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| 7. |
- Palm, Bruna, et al.
(author)
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Inflated Rayleigh Distribution for SAR Imagery Modeling
- 2022
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In: International Geoscience and Remote Sensing Symposium (IGARSS 2022). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781665427920 ; , s. 44-47
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Conference paper (peer-reviewed)abstract
- Synthetic aperture radars (SAR) data plays an important role in remote sensing applications. It is common knowledge that SAR image amplitude pixels can be approximately modeled by the Rayleigh distribution. However, this model is contin-uous and does not accommodate points with non-zero prob-ability, such as a null pixel amplitude value. Thus, in this paper, we propose an inflated Rayleigh distribution for SAR image modeling that is based on a mixed continuous-discrete distribution and can be used to fit signals with observed values on [0, infty). The maximum likelihood approach is considered to estimate the parameters of the proposed distribution. An empirical experiment with a SAR image is also presented and discussed. © 2022 IEEE.
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| 8. |
- Palm, Bruna, et al.
(author)
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Robust Rayleigh Regression Method for SAR Image Processing in Presence of Outliers
- 2022
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In: IEEE Transactions on Geoscience and Remote Sensing. - : Institute of Electrical and Electronics Engineers (IEEE). - 0196-2892 .- 1558-0644. ; 60
-
Journal article (peer-reviewed)abstract
- The presence of outliers (anomalous values) in synthetic aperture radar (SAR) data and the misspecification in statistical image models may result in inaccurate inferences. To avoid such issues, the Rayleigh regression model based on a robust estimation process is proposed as a more realistic approach to model this type of data. This article aims at obtaining Rayleigh regression model parameter estimators robust to the presence of outliers. The proposed approach considered the weighted maximum likelihood method and was submitted to numerical experiments using simulated and measured SAR images. Monte Carlo simulations were employed for the numerical assessment of the proposed robust estimator performance in finite signal lengths, their sensitivity to outliers, and the breakdown point. For instance, the nonrobust estimators show a relative bias value 65-fold larger than the results provided by the robust approach in corrupted signals. In terms of sensitivity analysis and break down point, the robust scheme resulted in a reduction of about 96% and 10%, respectively, in the mean absolute value of both measures, in compassion to the nonrobust estimators. Moreover, two SAR datasets were used to compare the ground type and anomaly detection results of the proposed robust scheme with competing methods in the literature. © 2022 IEEE.
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| 9. |
- Sjogren, Thomas K., et al.
(author)
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Change Detection for Monostatic Pursuit SAR GMTI-Theories and Experimental Results
- 2022
-
In: IEEE Transactions on Geoscience and Remote Sensing. - : Institute of Electrical and Electronics Engineers (IEEE). - 0196-2892 .- 1558-0644. ; 60
-
Journal article (peer-reviewed)abstract
- Monostatic pursuit refers to the operating mode formed by two monostatic synthetic aperture radar (SAR) systems that follow an identical orbit with a separation in a time of several seconds. The detected changes between SAR scenes with several seconds of time difference are most likely the changes caused by ground moving targets. Hence, this operating mode opens an opportunity to detect ground moving targets by SAR change detection methods. This article investigates this possibility to detect ground moving targets using change detection and to combine change detection and ground moving target indication (GMTI) for GMTI. In this combination, a GMTI method will help to classify the detected changes obtained with a change detection method. Some GMTI results are provided in the article based on the measurements in the monostatic pursuit mode with deployed targets, conducted by TerraSAR-X and TanDEM-X in Sweden in early 2015.
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| 10. |
- Vu, Viet Thuy, 1977-, et al.
(author)
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Fourier Transform of SAR Data Cube and 3D Range Migration Algorithm
- 2022
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In: IEEE Transactions on Aerospace and Electronic Systems. - : Institute of Electrical and Electronics Engineers Inc.. - 0018-9251 .- 1557-9603. ; 58:3, s. 2584-2591
-
Journal article (peer-reviewed)abstract
- To develop a 3-D imaging synthetic aperture radar(SAR) algorithm, a theoretical expression for a Fourier transform of data cube is required. In this article, we introduce a function representing the Fourier transform of 3-D SAR data cube. The function is derived using the method of stationary phase and similar to the one used for 2-D data matrix. For verification and evaluation, a 3-D range migration algorithm using this function for bulk compression is examined. The simulation results based on the parameters of an experimental terahertz indoor SAR testbed show that the algorithm can well focus the 3-D image and, hence, verify the derived function. The image quality assessments such as spatial resolutions and peak sidelobe ratio are used to further evaluate the function and the algorithm. The measured results are compared with the ones provided by a backprojection algorithm.
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