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| Citation: | LIAO Xingxing, LIU Zhe, and WU Junjie. Azimuth unambiguity suppression for low-oversampled Staggered SAR images[J]. Journal of Radars, 2021, 10(6): 874–884. doi: 10.12000/JR21106
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Azimuth Unambiguity Suppression for Low-oversampled Staggered SAR Images
DOI: 10.12000/JR21106
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Abstract
Low-oversampled staggered synthetic aperture radar can achieve continuously observed high-resolution and wide-swath imaging by utilizing the variable pulse repetition interval to distribute blind ranges. Moreover, adopting a low oversampling ratio can reduce the data storage requirements, contributing to its research significance. However, non-uniform sampling, echo data loss, and non-ideal Azimuth Antenna Pattern (AAP) cause severe azimuth ambiguities in a directly focused image. This study proposes a compressive sensing-based method with better ambiguity removal performance and higher efficiency compared to existing methods. First, an Innovative Frequency-Domain Model (IFDM) is constructed, which accurately describes the non-uniform sampling, echo data loss, and coupled range cell migration. Based on the IFDM, an optimization problem is constructed and solved by the two-dimensional fast iterative shrinkage thresholding algorithm to remove the ambiguity caused by non-uniform sampling and echo data loss. Subsequently, selective filtering is used to suppress the ambiguity caused by the AAP. The experiments demonstrate that the proposed method can more effectively and efficiently suppress the azimuth ambiguities compared to existing methods. -
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References
[1] VILLANO M, KRIEGER G, and MOREIRA A. Staggered SAR: High-resolution wide-swath imaging by continuous PRI variation[J]. IEEE Transactions on Geoscience and Remote Sensing, 2014, 52(7): 4462–4479. doi: 10.1109/TGRS.2013.2282192[2] HUBER S, DE ALMEIDA F Q, VILLANO M, et al. Tandem-L: A technical perspective on future spaceborne SAR sensors for earth observation[J]. IEEE Transactions on Geoscience and Remote Sensing, 2018, 56(8): 4792–4807. doi: 10.1109/TGRS.2018.2837673[3] LUO Xiulian, WANG Robert, XU Wei, et al. Modification of multichannel reconstruction algorithm on the SAR with linear variation of PRI[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014, 7(7): 3050–3059. doi: 10.1109/JSTARS.2014.2298242[4] VILLANO M, KRIEGER G, JÄGER M, et al. Staggered SAR: Performance analysis and experiments with real data[J]. IEEE Transactions on Geoscience and Remote Sensing, 2017, 55(11): 6617–6638. doi: 10.1109/TGRS.2017.2731047[5] WANG Xiangyu, WANG Robert, DENG Yunkai, et al. SAR signal recovery and reconstruction in staggered mode with low oversampling factors[J]. IEEE Geoscience and Remote Sensing Letters, 2018, 15(5): 704–708. doi: 10.1109/LGRS.2018.2805311[6] PINHEIRO M, PRATS-IRAOLA P, RODRIGUEZ-CASSOLA M, et al. Analysis of low-oversampled staggered SAR data[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020, 13: 241–255. doi: 10.1109/JSTARS.2019.2959092[7] STOICA P, LI Jian, and LING Jun. Missing data recovery via a nonparametric iterative adaptive approach[J]. IEEE Signal Processing Letters, 2009, 16(4): 241–244. doi: 10.1109/LSP.2009.2014114[8] CANDES E J and WAKIN M B. An introduction to compressive sampling[J]. IEEE Signal Processing Magazine, 2008, 25(2): 21–30. doi: 10.1109/MSP.2007.914731[9] HERMAN M A and STROHMER T. High-resolution radar via compressed sensing[J]. IEEE Transactions on Signal Processing, 2009, 57(6): 2275–2284. doi: 10.1109/TSP.2009.2014277[10] WEI Shunjun, ZHANG Xiaoling, SHI Jun, et al. Sparse reconstruction for SAR imaging based on compressed sensing[J]. Progress in Electromagnetics Research, 2010, 109: 63–81. doi: 10.2528/PIER10080805[11] FANG Jian, XU Zongben, ZHANG Bingchen, et al. Fast compressed sensing SAR imaging based on approximated observation[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014, 7(1): 352–363. doi: 10.1109/JSTARS.2013.2263309[12] DONG Xiao and ZHANG Yunhua. A novel compressive sensing algorithm for SAR imaging[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014, 7(2): 708–720. doi: 10.1109/JSTARS.2013.2291578[13] 顾福飞, 张群, 杨秋, 等. 基于NCS算子的大斜视SAR压缩感知成像方法[J]. 雷达学报, 2016, 5(1): 16–24. doi: 10.12000/JR15035GU Fufei, ZHANG Qun, YANG Qiu, et al. Compressed sensing imaging algorithm for high-squint SAR based on NCS operator[J]. Journal of Radars, 2016, 5(1): 16–24. doi: 10.12000/JR15035[14] 胡静秋, 刘发林, 周崇彬, 等. 一种新的基于Omega-K算法的稀疏场景压缩感知SAR成像方法(英文)[J]. 雷达学报, 2017, 6(1): 25–33. doi: 10.12000/JR16027HU Jingqiu, LIU Falin, ZHOU Chongbin, et al. CS-SAR imaging method based on inverse Omega-K algorithm[J]. Journal of Radars, 2017, 6(1): 25–33. doi: 10.12000/JR16027[15] ABERMAN K and ELDAR Y C. Sub-Nyquist SAR via Fourier domain range Doppler processing[J]. IEEE Transactions on Geoscience and Remote Sensing, 2017, 55(11): 6228–6244. doi: 10.1109/TGRS.2017.2723620[16] YANG Xiaoyu, LI Gang, SUN Jinping, et al. High-resolution and wide-swath SAR imaging via Poisson disk sampling and iterative shrinkage thresholding[J]. IEEE Transactions on Geoscience and Remote Sensing, 2019, 57(7): 4692–4704. doi: 10.1109/TGRS.2019.2892471[17] ZHANG Bingchen, JIANG Chenglong, ZHANG Zhe, et al. Azimuth ambiguity suppression for SAR imaging based on group sparse reconstruction[C]. 2nd International Workshop on Compressed Sensing applied to Radar (CoSeRa 2013), Bonn, Germany, 2013.[18] WIMALAJEEWA T, ELDAR Y C, and VARSHNEY P K. Recovery of sparse matrices via matrix sketching[J]. arXiv: 1311.2448, 2013.[19] CUMMING L G, WONG F H, 洪文, 胡东辉, 译. 合成孔径雷达成像——算法与实现[M]. 北京: 电子工业出版社, 2007: 90–91.CUMMING L G, WONG F H, HONG Wen, HU Donghui, translation. Digital Processing of Synthetic Aperture Radar Data: Algorithms and Implementation[M]. Beijing: Publishing House of Electronics Industry, 2007: 90–91.[20] DI MARTINO G, IODICE A, RICCIO D, et al. Filtering of azimuth ambiguity in stripmap synthetic aperture radar images[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014, 7(9): 3967–3978. doi: 10.1109/JSTARS.2014.2320155[21] DAUBECHIES I. Orthonormal bases of compactly supported wavelets[J]. Communications on Pure and Applied Mathematics, 1988, 41(7): 909–996. doi: 10.1002/cpa.3160410705[22] LIU Zhe, LIAO Xingxing, and WU Junjie. Image reconstruction for low-oversampled staggered SAR via HDM-FISTA[J]. IEEE Transactions on Geoscience and Remote Sensing, 2021. doi: 10.1109/TGRS.2021.3065575.[23] GUARNIERI A M. Adaptive removal of azimuth ambiguities in SAR images[J]. IEEE Transactions on Geoscience and Remote Sensing, 2005, 43(3): 625–633. doi: 10.1109/TGRS.2004.842476[24] BECK A and TEBOULLE M. A fast iterative shrinkage-thresholding algorithm for linear inverse problems[J]. SIAM Journal on Imaging Sciences, 2009, 2(1): 183–202. doi: 10.1137/080716542[25] HANSEN P C and O’LEARY D P. The use of the L-curve in the regularization of discrete Ill-posed problems[J]. SIAM Journal on Scientific Computing, 1993, 14(6): 1487–1503. doi: 10.1137/0914086 -
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- Figure 1. Map of azimuth antenna pattern aliasing for Staggered SAR
- Figure 2. Azimuth profiles of reconstructed results for a point target
- Figure 3. Imaging result of the simulated data of the 20 km×20.5 km scene
- Figure 4. Larger image of imaging result of “Zone 1” in the 20 km×20.5 km scene and comparison of azimuth profiles
- Figure 5. Larger image of reconstructed result of “Zone 2” in the 20 km×20.5 km scene