Citation: | CAI Xiang, WEI Shunjun, WEN Yanbo, et al. Precise reconstruction method for hidden targets based on non-line-of-sight radar 3D imaging[J]. Journal of Radars, 2024, 13(4): 791–806. doi: 10.12000/JR24060 |
[1] |
WEI Shunjun, WEI Jinshan, LIU Xinyuan, et al. Nonline-of-sight 3-D imaging using millimeter-wave radar[J]. IEEE Transactions on Geoscience and Remote Sensing, 2022, 60: 5106518. doi: 10.1109/TGRS.2021.3112579.
|
[2] |
孔令讲, 郭世盛, 陈家辉, 等. 多径利用雷达目标探测技术综述与展望[J]. 雷达学报(中英文), 2024, 13(1): 23–45. doi: 10.12000/JR23134.
KONG Lingjiang, GUO Shisheng, CHEN Jiahui, et al. Overview and prospects of multipath exploitation radar target detection technology[J]. Journal of Radars, 2024, 13(1): 23–45. doi: 10.12000/JR23134.
|
[3] |
杨建宇. 雷达技术发展规律和宏观趋势分析[J]. 雷达学报, 2012, 1(1): 19–27. doi: 10.3724/SP.J.1300.2012.20010.
Yang Jianyu. Development laws and macro trends analysis of radar technology[J]. Journal of Radars, 2012, 1(1): 19–27. doi: 10.3724/SP.J.1300.2012.20010.
|
[4] |
丁赤飚, 仇晓兰, 吴一戎. 全息合成孔径雷达的概念、体制和方法[J]. 雷达学报, 2020, 9(3): 399–408. doi: 10.12000/JR20063.
DING Chibiao, QIU Xiaolan, and WU Yirong. Concept, system, and method of holographic synthetic aperture radar[J]. Journal of Radars, 2020, 9(3): 399–408. doi: 10.12000/JR20063.
|
[5] |
丁赤飚, 仇晓兰, 徐丰, 等. 合成孔径雷达三维成像—从层析、阵列到微波视觉[J]. 雷达学报, 2019, 8(6): 693–709. doi: 10.12000/JR19090.
DING Chibiao, QIU Xiaolan, XU Feng, et al. Synthetic aperture radar three-dimensional imaging—from TomoSAR and array InSAR to microwave vision[J]. Journal of Radars, 2019, 8(6): 693–709. doi: 10.12000/JR19090.
|
[6] |
VELTEN A, WILLWACHER T, GUPTA O, et al. Recovering three-dimensional shape around a corner using ultrafast time-of-flight imaging[J]. Nature communications, 2012, 3(1): 745. doi: 10.1038/ncomms1747.
|
[7] |
KATZ O, HEIDMANN P, FINK M, et al. Non-invasive single-shot imaging through scattering layers and around corners via speckle correlations[J]. Nature photonics, 2014, 8(10): 784–790. doi: 10.1038/nphoton.2014.189.
|
[8] |
YEDIDIA A B, BARADAD M, THRAMPOULIDIS C, et al. Using unknown occluders to recover hidden scenes[C]. 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Long Beach, USA, 2019: 12223–12231. doi: 10.1109/CVPR.2019.01251.
|
[9] |
KIRMANI A, HUTCHISON T, DAVIS J, et al. Looking around the corner using transient imaging[C]. 2009 IEEE 12th International Conference on Computer Vision, Kyoto, Japan, 2009: 159–166. doi: 10.1109/ICCV.2009.5459160.
|
[10] |
LIU Xintong, WANG Jianyu, LI Zhupeng, et al. Non-line-of-sight reconstruction with signal-object collaborative regularization[J]. Light: Science & Applications, 2021, 10(1): 198. doi: 10.1038/s41377-021-00633-3.
|
[11] |
LINDELL D B, WETZSTEIN G, and KOLTUN V. Acoustic non-line-of-sight imaging[C]. 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Long Beach, USA, 2019: 6773–6782. doi: 10.1109/CVPR.2019.00694.
|
[12] |
ADIB F and KATABI D. See through walls with WiFi![C]. ACM SIGCOMM 2013 conference on SIGCOMM, Hong Kong, China, 2013: 75–86. doi: 10.1145/2486001.2486039.
|
[13] |
PAULI M, GÖTTEL B, SCHERR S, et al. Miniaturized millimeter-wave radar sensor for high-accuracy applications[J]. IEEE Transactions on Microwave Theory and Techniques, 2017, 65(5): 1707–1715. doi: 10.1109/TMTT.2017.2677910.
|
[14] |
WANG Xiao, XU Linhai, SUN Hongbin, et al. On-road vehicle detection and tracking using MMW radar and monovision fusion[J]. IEEE Transactions on Intelligent Transportation Systems, 2016, 17(7): 2075–2084. doi: 10.1109/TITS.2016.2533542.
|
[15] |
LEIGSNERING M, AHMAD F, AMIN M, et al. Multipath exploitation in through-the-wall radar imaging using sparse reconstruction[J]. IEEE Transactions on Aerospace and Electronic Systems, 2014, 50(2): 920–939. doi: 10.1109/TAES.2013.120528.
|
[16] |
SUME A, GUSTAFSSON M, HERBERTHSON M, et al. Radar detection of moving targets behind corners[J]. IEEE Transactions on Geoscience and Remote Sensing, 2011, 49(6): 2259–2267. doi: 10.1109/TGRS.2010.2096471.
|
[17] |
ZETIK R, ESCHRICH M, JOVANOSKA S, et al. Looking behind a corner using multipath-exploiting UWB radar[J]. IEEE Transactions on Aerospace and Electronic Systems, 2015, 51(3): 1916–1926. doi: 10.1109/TAES.2015.140303.
|
[18] |
YANG Xiaqing, FAN Shihao, GUO Shisheng, et al. NLOS target localization behind an L-shaped corner with an L-band UWB radar[J]. IEEE Access, 2020, 8: 31270–31286. doi: 10.1109/ACCESS.2020.2973046.
|
[19] |
LI Songlin, GUO Shisheng, CHEN Jiahui, et al. Multiple targets localization behind L-shaped corner via UWB radar[J]. IEEE Transactions on Vehicular Technology, 2021, 70(4): 3087–3100. doi: 10.1109/TVT.2021.3068266.
|
[20] |
KAMANN A, HELD P, PERRAS F, et al. Automotive radar multipath propagation in uncertain environments[C]. 2018 21st International Conference on Intelligent Transportation Systems (ITSC), Maui, USA, 2018: 859–864. doi: 10.1109/ITSC.2018.8570016.
|
[21] |
CAI Xiang, WEI Shunjun, WEN Yanbo, et al. Bayesian-Based 3-D MMW radar imaging of non-line-of-sight environments[C]. 2023 Cross Strait Radio Science and Wireless Technology Conference (CSRSWTC), Guilin, China, 2023: 1–3. doi: 10.1109/CSRSWTC60855.2023.10427181.
|
[22] |
CAI Xiang, WEI Shunjun, LIU Xinyuan, et al. Compressed sensing imaging of MMW automotive radar via non-line-of-sight observation[C]. 2023 IEEE International Geoscience and Remote Sensing Symposium, Pasadena, USA, 2023: 1225–1228. doi: 10.1109/IGARSS52108.2023.10282596.
|
[23] |
WEN Yanbo, WEI Shunjun, WEI Jinshan, et al. Non-line-of-sight imaging of hidden moving target using millimeter-wave inverse synthetic aperture radar[C]. 2022 IEEE International Geoscience and Remote Sensing Symposium, Kuala Lumpur, Malaysia, 2022: 555–558. doi: 10.1109/IGARSS46834.2022.9883939.
|
[24] |
LIN Yuqing, LUO Yitong, QIU Xiaolan, et al. Non-line-of-sight target imaging in tomographic SAR by multipath signal analysis[C]. 2023 IEEE International Geoscience and Remote Sensing Symposium, Pasadena, USA, 2023: 7761–7764. doi: 10.1109/IGARSS52108.2023.10281638.
|
[25] |
YEGULALP A F. Fast backprojection algorithm for synthetic aperture radar[C]. 1999 IEEE Radar Conference. Radar into the Next Millennium (Cat. No99CH36249), Waltham, USA, 1999: 60–65. doi: 10.1109/NRC.1999.767270.
|
[26] |
FRANCESCHETTI G and SCHIRINZI G. A SAR processor based on two-dimensional FFT codes[J]. IEEE Transactions on Aerospace and Electronic Systems, 1990, 26(2): 356–366. doi: 10.1109/7.53462.
|
[27] |
LOPEZ-SANCHEZ J M and FORTUNY-GUASCH J. 3-D radar imaging using range migration techniques[J]. IEEE Transactions on Antennas and Propagation, 2000, 48(5): 728–737. doi: 10.1109/8.855491.
|
[28] |
BROWN W M. Synthetic aperture radar[J]. IEEE Transactions on Aerospace and Electronic Systems, 1967, AES-3(2): 217–229. doi: 10.1109/TAES.1967.5408745.
|
[29] |
DONOHO D L. Compressed sensing[J]. IEEE Transactions on Information Theory, 2006, 52(4): 1289–1306. doi: 10.1109/TIT.2006.871582.
|
[30] |
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.
|
[31] |
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.
|
[32] |
ÇETIN M, STOJANOVIĆ I, ÖNHON N Ö, et al. Sparsity-driven synthetic aperture radar imaging: Reconstruction, autofocusing, moving targets, and compressed sensing[J]. IEEE Signal Processing Magazine, 2014, 31(4): 27–40. doi: 10.1109/MSP.2014.2312834.
|
[33] |
BARANIUK R and STEEGHS P. Compressive radar imaging[C]. 2007 IEEE Radar Conference, Waltham, USA, 2007: 128–133. doi: 10.1109/RADAR.2007.374203.
|
[34] |
XU Gang, XIA Xianggen, and WEI Hong. Nonambiguous SAR image formation of maritime targets using weighted sparse approach[J]. IEEE Transactions on Geoscience and Remote Sensing, 2018, 56(3): 1454–1465. doi: 10.1109/TGRS.2017.2763147.
|
[35] |
PU Wei, WU Junjie, WANG Xiaodong, et al. Joint sparsity-based imaging and motion error estimation for BFSAR[J]. IEEE Transactions on Geoscience and Remote Sensing, 2019, 57(3): 1393–1408. doi: 10.1109/TGRS.2018.2866437.
|
[36] |
WEI Shunjun, ZHANG Xiaoling, and SHI Jun. Sparse autofocus via Bayesian learning iterative maximum and applied for LASAR 3-D imaging[C]. 2014 IEEE Radar Conference, Cincinnati, USA, 2014: 0666–0669. doi: 10.1109/RADAR.2014.6875674.
|
[37] |
STRONG D and CHAN T. Edge-preserving and scale-dependent properties of total variation regularization[J]. Inverse Problems, 2003, 19(6): S165–S187. doi: 10.1088/0266-5611/19/6/059.
|
[38] |
OSHER S, BURGER M, GOLDFARB D, et al. An iterative regularization method for total variation-based image restoration[J]. Multiscale Modeling & Simulation, 2005, 4(2): 460–489. doi: 10.1137/040605412.
|
[39] |
WANG Mou, WEI Shunjun, LIANG Jiadian, et al. RMIST-Net: Joint range migration and sparse reconstruction network for 3-D mmW imaging[J]. IEEE Transactions on Geoscience and Remote Sensing, 2022, 60: 5205117. doi: 10.1109/TGRS.2021.3068405.
|
[40] |
WANG Yingzhou, LI Lijun, and GONG Ke. Narrowband experimental study on millimeter-wave indoor propagation[C]. 1998 International Conference on Communication Technology, Beijing, China, 1998: 5. doi: 10.1109/ICCT.1998.741269.
|
[41] |
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.
|
[42] |
CALVETTI D, REICHEL L, and SHUIBI A. L-curve and curvature bounds for Tikhonov regularization[J]. Numerical Algorithms, 2004, 35(2): 301–314. doi: 10.1023/B:NUMA.0000021764.16526.47.
|
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