双基地ISAR稀疏孔径机动目标MTRC补偿成像算法

doi:10.12305/j.issn.1001-506X.2023.07.12

Abstract

Abstract:

Aiming at the problem that it is difficult to compensate the migration through range cells (MTRC) of maneuvering target under the condition of sparse aperture in bistatic inverse synthetic aperture radar (Bi-ISAR) system, a compensated imaging method combining Keystone transform and weighted l₁ norm sparse constrained optimization algorithm is proposed. Based on the Bi-ISAR sparse aperture echo data after translation compensation, assuming that each pixel of the target image is sparse and non identically distributed, a variable scale Fourier transform sparse basis with Keystone transform parameters and time-varying bistatic angle is established for each range cell, and the weighted l₁ norm sparse constrained optimization algorithm is used to recover the azimuth scattering coefficient imaging. Experimental results show the effectiveness and robustness of the proposed algorithm.

Key words: bistatic inverse synthetic aperture radar (Bi-ISAR), sparse aperture, maneuvering target, migration through range cells (MTRC)

CLC Number:

TN957.52

Hanshen ZHU, Wenhua HU, Baofeng GUO, Liting JIAO, Xiaoxiu ZHU, Chang'an ZHU. Bistatic ISAR sparse aperture maneuvering target MTRC compensation imaging algorithm[J]. Systems Engineering and Electronics, 2023, 45(7): 2022-2030.

Figures/Tables 6

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Table 1

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Table 2

References 31

1	ZHANG S S , ZHANG W , ZONG Z L , et al. High-resolution bistatic ISAR imaging based on two-dimensional compressed sensing[J]. IEEE Trans.on Antennas and Propagation, 2015, 63 (5): 2098- 2111. doi: 10.1109/TAP.2015.2408337
2	KANG M S , LEE S H , KIM K T , et al. Bistatic ISAR imaging and scaling of highly maneuvering target with complex motion via compressive sensing[J]. IEEE Trans.on Aerospace and Electronic Systems, 2016, 54 (6): 2809- 2826.
3	KANG B S , RYU B H , KIM K T . Bistatic ISAR imaging for non-uniformly rotating targets[J]. IEEE Trans.on Aerospace and Electronic Systems, 2019, 55 (4): 1972- 1988. doi: 10.1109/TAES.2018.2880027
4	朱晓秀, 胡文华, 郭宝锋, 等. 基于快速SBL的双基地ISAR成像[J]. 雷达科学与技术, 2019, 17 (3): 290- 298.
	ZHU X X , HU W H , GUO B F , et al. Bistatic ISAR imaging based on fast SBL algorithm with sparse aperture[J]. Radar Science and Technology, 2019, 17 (3): 290- 298.
5	SHI L , ZHU X X , SHANG C X , et al. High-resolution bistatic ISAR imaging of a space target with sparse aperture[J]. Electronics, 2017, 8 (8): 874- 893.
6	陈文峰, 陈阿磊, 郑岱堃, 等. 参数化稀疏表示的双基地ISAR机动目标成像方法[J]. 空军预警学院学报, 2020, 34 (3): 157- 162. doi: 10.3969/j.issn.2095-5839.2020.03.001
	CHEN W F , CHEN A L , ZHENG D K , et al. Bistatic ISAR maneuvering target imaging method based on parameterized sparse representation[J]. Journal of Air Force Early Warning Academy, 2020, 34 (3): 157- 162. doi: 10.3969/j.issn.2095-5839.2020.03.001
7	QIAN J , HUANG S Y , WANG L , et al. Super-resolution ISAR imaging for maneuvering target based on deep learning assisted time-frequency analysis[J]. IEEE Trans.on Geoscience and Remote Sensing, 2021, 99, 1- 14.
8	PERRY R P , DIPIETRO R C , FANTE R L . SAR imaging of moving targets[J]. IEEE Trans.on Aerospace and Electronic Systems, 1999, 35 (1): 188- 200. doi: 10.1109/7.745691
9	ZHANG S H , LIU Y X , LI X . Sparse aperture InISAR imaging via sequential multiple sparse Bayesian learning[J]. Sensors, 2017, 17 (10): 2295- 2315. doi: 10.3390/s17102295
10	ZENG C Z , ZHU W G , JIA X , et al. Sparse aperture ISAR imaging method based on joint constraints of sparsity and low rank[J]. IEEE Trans.on Geoscience and Remote Sensing, 2020, 59 (1): 168- 181.
11	ZHANG S H , LIU Y X , LI X . Autofocusing for sparse aperture ISAR imaging based on joint constraint of sparsity and minimum rntropy[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2017, 10 (3): 998- 1011. doi: 10.1109/JSTARS.2016.2598880
12	CHEN W F , LV M J , YANG J , et al. Sparse aperture bistatic ISAR imaging under low signal-to-noise ratio condition[J]. Journal of Applied Remote Sensing, 2020, 14 (3): 1- 15.
13	DONOHO D L . Compressed sensing[J]. IEEE Trans.on Information Theory, 2006, 52 (4): 1289- 1306. doi: 10.1109/TIT.2006.871582
14	朱小鹏, 张群, 朱仁飞, 等. 双站ISAR越距离单元徙动分析与校正算法[J]. 系统工程与电子技术, 2010, 32 (9): 1828- 1832. doi: 10.3969/j.issn.1001-506X.2010.09.09
	ZHU X P , ZHANG Q , ZHU R F , et al. Study on correction algorithm of migration through resolution cell in bistatic-ISAR[J]. Systems Engineering and Electronics, 2010, 32 (9): 1828- 1832. doi: 10.3969/j.issn.1001-506X.2010.09.09
15	韩宁, 尚朝轩, 何强, 等. 双基地ISAR越距离单元徙动分析与校正方法[J]. 火力指挥与控制, 2013, 38 (3): 49- 52.
	HAN N , SHANG C X , HE Q , et al. Study on correction method of bistatic ISAR migration through resolution cell for space target[J]. Fire Control & Command Control, 2013, 38 (3): 49- 52.
16	HONG T, ZHANG S H, LIU Y X. MTRC compensation for sparse aperture ISAR imaging[C]//Proc. of the International Conference on Wireless Communications and Smart Grid, 2020: 52-56.
17	王映雪. 压缩感知重构算法研究及CoSaMP算法改进[D]. 天津: 天津大学, 2017.
	WANG Y X. Research on compressed sensing reconstruction algorithm and improvement of CoSaMP algorithm[D]. Tianjin: Tianjin University, 2017.
18	WANG B P , FANG Y , SUN C , et al. Narrowband radar imaging for spinning targets based on compressed sensing[J]. Journal of Remote Sensing, 2015, 13 (7): 34- 42.
19	朱晓秀, 胡文华, 马俊涛, 等. 基于Laplace先验的复贝叶斯压缩感知ISAR高分辨成像算法[J]. 系统工程与电子技术, 2018, 40 (12): 2689- 2698.
	ZHU X X , HU W H , MA J T , et al. High-resolution algorithm for ISAR imaging based on complex Bayesian compressed sensing using Laplace priors[J]. Systems Engineering and Electronics, 2018, 40 (12): 2689- 2698.
20	王勇, 黄鑫. FMCW-ISAR对舰船目标成像脉内补偿方法研究[J]. 雷达学报, 2019, 8 (3): 373- 380.
	WANG Y , HUANG X . Research on in-pulse compensation method for imaging ship targets in FMCW-ISAR[J]. Journal of Radars, 2019, 8 (3): 373- 380.
21	俞翔. ISAR运动补偿和成像新方法的研究[D]. 南京: 南京航空航天大学, 2013.
	YU X. Research on new methods for ISAR motion compensation and imaging[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2013.
22	侯颖妮, 杨予昊, 于俊朋. 基于压缩感知的稀疏采样数据大转角ISAR成像研究[J]. 现代雷达, 2018, 40 (12): 41- 45.
	HOU Y N , YANG Y H , YU J P . A study on wide angle ISAR imaging of sparse sampling data based on compressive sensing[J]. Modern Radars, 2018, 40 (12): 41- 45.
23	郭宝锋, 尚朝轩, 高梅国, 等. 机动目标双基地ISAR越距离单元徙动校正算法[J]. 数据采集与处理, 2014, 29 (4): 562- 569.
	GUO B F , SHANG C X , GAO M G , et al. Correction algorithm of migration through resolution cells in bistatic ISAR of maneuvering target[J]. Journal of Data Acquisition & Processing, 2014, 29 (4): 562- 569.
24	郭宝锋, 尚朝轩, 王俊岭, 等. 双基地角时变下的逆合成孔径雷达越分辨单元徙动校正算法[J]. 物理学报, 2014, 63 (23): 1- 11.
	GUO B F , SHANG C X , WANG J L , et al. Correction of migration through resolution cell in bistatic inverse synthetic aperture radar in the presence of time-varying bistatic angle[J]. Acta Physica Sinica, 2014, 63 (23): 1- 11.
25	薛东方, 朱晓秀, 胡文华, 等. 基于加权l₁范数优化的双基地ISAR稀疏成像算法[J]. 系统工程与电子技术, 2021, 43 (4): 944- 953.
	XUE D F , ZHU X X , HU W H , et al. Bi-ISAR imaging based on weighted l₁ norm optimization algorithm[J]. Systems Engineering and Electronics, 2021, 43 (4): 944- 953.
26	ZHANG L , QIAO Z J , XING M D , et al. High-resolution ISAR imaging by exploiting sparse apertures[J]. IEEE Trans.on Antennas and Propagation, 2012, 60 (2): 997- 1008.
27	保铮, 邢孟道, 王彤. 雷达成像技术[M]. 北京: 电子工业出版社, 2005.
	BAO Z , XING M D , WANG T . Radar imaging technology[M]. Beijing: Publishing House of Electronics Industry, 2005.
28	WU Q. A nonlinear conjugate gradient method without line search and its global convergence[C]//Proc. of the International Conference on Computational and Information Sciences, 2011: 1148-1152.
29	CETIN M , KARL W C . Feature-enhanced synthetic aperture radar image formation based on non-quadratic regularization[J]. IEEE Trans.on Image Processing, 2002, 10 (4): 623- 631.
30	徐刚, 包敏, 李亚超, 等. 基于贝叶斯估计的高精度ISAR成像[J]. 系统工程与电子技术, 2011, 33 (11): 2382- 2388.
	XU G , BAO M , LI Y C , et al. High precision ISAR imaging via Bayesian statistics[J]. Systems Engineering and Electronics, 2011, 33 (11): 2382- 2388.
31	张清河, 于士奇, 时李萍, 等. 对比源框架下的多任务贝叶斯压缩感知微波成像方法[J]. 电子学报, 2020, 48 (11): 2208- 2214.
	ZHANG Q H , YU S Q , SHI L P , et al. Microwave imaging by multitask Bayesian compressed sensing within contrast source framework[J]. Acta Electronica Sinica, 2020, 48 (11): 2208- 2214.

成像参数	取值	成像参数	取值
载频/GHz	10	脉冲宽度/μs	20
带宽/MHz	800	脉冲重复频率/Hz	50
采样率/GHz	1	距离向分辨率/m	0.206 7
成像时间/s	10	方位向分辨率/m	0.262 8

衡量指标	算法	SNR/dB
衡量指标	算法	20	10	5	0
图像熵	EM-VB	2.874 5	2.901 4	2.952 4	3.052 4
	CoSaMP	2.327 1	2.572 4	2.677 5	2.895 2
	本文算法	2.012 4	2.195 7	2.342 4	2.467 5
TBR	EM-VB	12.349	11.427 5	10.106 5	9.562 4
	CoSaMP	24.795 1	21.224 7	18.032 6	12.774 5
	本文算法	29.336 5	26.716 3	23.425 7	20.454 5

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[8]	Dongfang XUE, Xiaoxiu ZHU, Wenhua HU, Baofeng GUO, Huiyan ZENG. Bi-ISAR imaging based on weighted l₁ norm optimization algorithm [J]. Systems Engineering and Electronics, 2021, 43(4): 944-953.
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Bistatic ISAR sparse aperture maneuvering target MTRC compensation imaging algorithm

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