Multi-static InISAR imaging for ships under sparse aperture

doi:10.23919/JSEE.2022.000055

Journal of Systems Engineering and Electronics ›› 2022, Vol. 33 ›› Issue (3): 575-584.doi: 10.23919/JSEE.2022.000055

收稿日期:2021-03-01 出版日期:2022-06-18 发布日期:2022-06-24

Multi-static InISAR imaging for ships under sparse aperture

Bingren JI(), Yong WANG*(), Bin ZHAO(), Rongqing XU()

¹ School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150001, China

Received:2021-03-01 Online:2022-06-18 Published:2022-06-24
Contact: Yong WANG E-mail:1455252058@qq.com;wangyong6012@hit.edu.cn;smith@riee.hit.edu.cn;xurongqing@hit.edu.cn
About author:|JI Bingren was born in 1992. He received his B.S. degree and M.S. degree in the Department of Electronic Information Engineering in 2014 and 2016 from Harbin Institute of Technology (HIT), Harbin, China. He is now pursuing his Ph.D. degree in the Department of Electronic Information Engineering from HIT. His current research interests include ISAR imaging, compressed sensing, and interferometric ISAR. E-mail: 1455252058@qq.com||WANG Yong was born in 1979. He received his B.S. degree and M.S. degree from Harbin Institute of Technology (HIT), Harbin, China, in 2002 and 2004, respectively, both in electronic engineering. He received his Ph.D. degree in information and communication engineering from HIT in 2008. He is currently a professor with the Institute of Electronic Engineering Technology in HIT. His main research interests are time frequency analysis of nonstationary signals, radar signal processing, and their application in synthetic aperture radar imaging. E-mail: wangyong6012@hit.edu.cn||ZHAO Bin was born in 1972. He received his B.S. degree and M.S. degree from Harbin Institute of Technology (HIT), Harbin, China, in 1988 and 1998, respectively, both in electronic engineering. He received his Ph.D. degree in information and communication engineering from HIT in 2008. He is currently a professor with the Institute of Electronic Engineering Technology in HIT. His main research interests are radar system control and synthetic aperture radar imaging. E-mail: smith@riee.hit.edu.cn||XU Rongqing was born in 1958. He received his B.S. and M.S. degrees in electronic engineering and his Ph.D. degree in information and communication engineering from Harbin Institute of Technology (HIT), Harbin, China, in 1982, 1984, and 1990, respectively. He is currently a professor with the Institute of Electronic Engineering Technology, HIT. His main research interest is radar signal processing. E-mail: xurongqing@hit.edu.cn
Supported by:
This work was supported by the National Natural Science Foundation of China (61871146)

摘要/Abstract

Abstract:

This paper concentrates on super-resolution imaging of the ship target under the sparse aperture situation. Firstly, a multi-static configuration is utilized to solve the coherent processing interval (CPI) problem caused by the slow-speed motion of ship targets. Then, we realize signal restoration and image reconstruction with the alternating direction method of multipliers (ADMM). Furthermore, we adopt the interferometric technique to produce the three-dimensional (3D) images of ship targets, namely interferometric inverse synthetic aperture radar (InISAR) imaging. Experiments based on the simulated data are utilized to verify the validity of the proposed method.

Key words: multi-static, sparse aperture, signal recovery, interferometric inverse synthetic aperture radar (InISAR), ship target, alternating direction method of multipliers (ADMM)

. [J]. Journal of Systems Engineering and Electronics, 2022, 33(3): 575-584.

Bingren JI, Yong WANG, Bin ZHAO, Rongqing XU. Multi-static InISAR imaging for ships under sparse aperture[J]. Journal of Systems Engineering and Electronics, 2022, 33(3): 575-584.

图/表 12

参考文献 26

1	CHEN C C, ANDREWS H C Target-motion induced radar imaging. IEEE Trans. on Aerospace and Electronic Systems, 1980, 16 (1): 2- 14.
2	ZHENG J B, SU T, ZHU W T, et al ISAR imaging of targets with complex motions based on the keystone time-chirp rate distribution. IEEE Geoscience and Remote Sensing Letters, 2014, 11 (7): 1275- 1279. doi: 10.1109/LGRS.2013.2291992
3	LI G, ZHANG H, WANG X Q, et al ISAR 2-D imaging of uniformly rotating targets via matching pursuit. IEEE Trans. on Aerospace and Electronic Systems, 2012, 48 (2): 1838- 1846. doi: 10.1109/TAES.2012.6178106
4	ZHENG J B, SU T, ZHANG L, et al ISAR imaging of targets with complex motion based on the chirp rate-quadratic chirp rate distribution. IEEE Trans. on Geoscience and Remote Sensing, 2014, 52 (11): 7276- 7289. doi: 10.1109/TGRS.2014.2310474
5	ZHENG J B, SU T, ZHU W T, et al Fast parameter estimation algorithm for cubic phase signal based on quantifying effects of Doppler frequency shift. Progress in Electromagnetics Research, 2013, 142, 57- 74. doi: 10.2528/PIER13061008
6	ZHANG L, DUAN J, QIAO Z J Phase adjustment and ISAR imaging of maneuvering targets with sparse apertures. IEEE Trans. on Aerospace and Electronic System, 2014, 50 (3): 1955- 1973. doi: 10.1109/TAES.2013.130115
7	ZENG C Z, ZHU W G, JIA X Sparse aperture ISAR imaging algorithm based on adaptive filtering framework. IET Radar, Sonar & Navigation, 2019, 13 (3): 445- 455. doi: 10.1049/iet-rsn.2018.5420
8	PRICKETT M J, CHEN C C Principles of inverse synthetic aperture radar imaging. Proc. of the Electronic Aerospace System Conference, 1980, 340- 345.
9	ZHU D Y, WANG L, YU Y, et al Robust ISAR range alignment via minimizing the entropy of the average range profile. IEEE Geoscience and Remote Sensing Papers, 2009, 6 (2): 204- 208. doi: 10.1109/LGRS.2008.2010562
10	WAHL D E, EICHEL P H, GHIGLIA D C, et al Phase gradient autofocus—a robust tool for high-resolution SAR phase correction. IEEE Trans. on Aerospace and Electronic System, 1994, 30 (3): 827- 835. doi: 10.1109/7.303752
11	YE W, YEO T S, BAO Z Weighted least-squares estimation of phase errors for SAR/ISAR autofocus. IEEE Trans. on. Geoscience and Remote Sensing, 1999, 37 (5): 2487- 2494. doi: 10.1109/36.789644
12	JAKOWATZ C V, WAHL D E Eigenvector method for maximum-likelihood estimation of phase errors in synthetic aperture radar imagery. Journal of the Optical Society of America, 1993, 10 (12): 2539- 2546. doi: 10.1364/JOSAA.10.002539
13	MARTORELLA M, BERIZZI F, HAYWOOD B Contrast maximization based technique for 2-D ISAR autofocusing. IEE Proceedings-Radar, Sonar and Navigation, 2005, 152 (4): 253- 262. doi: 10.1049/ip-rsn:20045123
14	LARSSON E G, STOICA P, LI J Amplitude spectrum estimation for two-dimensional gapped data. IEEE Trans. on Signal Processing, 2002, 50 (6): 1343- 1353. doi: 10.1109/TSP.2002.1003059
15	BARANIUK R, STEEGHS P Compressive radar imaging. Proc. of the IEEE Radar Conference, 2007, 128- 133.
16	DONOHO D L Compressed sensing. IEEE Trans. on Information Theory, 2006, 52 (4): 1289- 1306. doi: 10.1109/TIT.2006.871582
17	CANDES E J, ROMBERG J, TAO T Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information. IEEE Trans. on Information Theory, 2006, 52 (2): 489- 509. doi: 10.1109/TIT.2005.862083
18	MORADIKIA M, SAMADI S, CETIN M Joint SAR imaging and multi-feature decomposition from 2-D under-sampled data via low-rankness plus sparsity priors. IEEE Trans. on Computational Imaging, 2018, 5 (1): 1- 16.
19	QIU W, ZHOU J X, FU Q Jointly using low-rank and sparsity priors for sparse inverse synthetic aperture radar imaging. IEEE Trans. on Image Processing, 2020, 29, 100- 115. doi: 10.1109/TIP.2019.2927458
20	LU X Y, ZHAO Y J, YANG J C An efficient method for single-channel SAR target reconstruction under severe deceptive jamming. IEEE Geoscience and Remote Sensing Letters, 2020, 17 (2): 237- 241. doi: 10.1109/LGRS.2019.2918838
21	LI Y C, WU R, XING M D Inverse synthetic aperture radar imaging of ship target with complex motion. IET Radar, Sonar & Navigation, 2008, 2 (6): 395- 403. doi: 10.1049/iet-rsn:20070101
22	WANG Y, LI X L Three-dimensional interferometric ISAR imaging for the ship target under the bi-static configuration. IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing, 2016, 9 (4): 1505- 1520. doi: 10.1109/JSTARS.2015.2513774
23	MA C Z, YEO T S, GUO Q Bistatic ISAR imaging incorporating interferometric 3-D imaging technique. IEEE Trans. on Geoscience and Remote Sensing, 2012, 50 (10): 3859- 3867. doi: 10.1109/TGRS.2012.2186304
24	QIU W, ZHOU J X, ZHAO H Z, et al Three-dimensional sparse turntable microwave imaging based on compressive sensing. IEEE Geoscience and Remote Sensing Letters, 2015, 12 (4): 826- 830. doi: 10.1109/LGRS.2014.2363238
25	XU G, XING M D, XIA X G Three-dimensional geometry and motion estimations of maneuvering targets for interferometric ISAR with sparse aperture. IEEE Trans. on Image Processing, 2016, 25 (5): 2005- 2020. doi: 10.1109/TIP.2016.2535362
26	WU Y L, ZHANG S S, KANG H Q. Fast marginalized sparse Bayesian learning for 3-D interferometric ISAR image formation via super-resolution ISAR imaging. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2015, 8(10): 4942–4951.

Parameter	Value	Parameter	Value
Range sampling frequency/MHz	25.6	Bandwidth/MHz	200
SNR/dB	25	Carrier frequency/GHz	10
Pulse number	256	Pulse repetition frequency/Hz	625
Pulse width/μs	10	The length of baseline/m	2

Parameter	Pitch	Roll	Yaw
Amplitude/radian	$1{\text{π}}$ /180	$1.5{\text{π} }$ /180	$3{\text{π}}$ /180
Period/s	6	12	14
Angular velocity/(radian/s)	$2{\text{π}}$ /6	$2{\text{π}}$ /12	$2{\text{π}}$ /14

Parameter	Pitch	Roll	Yaw
Amplitude/radian	$ 2{\text{π}} $ /180	$3{\text{π} }$ /180	$4{\text{π}} $ /180
Period/s	6	12	14
Angular velocity/(radian/s)	$2{\text{π}} $ /6	$2{\text{π}} $ /12	$2{\text{π}} $ /14

Figure	RM	RM1
Fig. 6	3.8269	3.8036
Fig. 7	3.9546	3.8103

Multi-static InISAR imaging for ships under sparse aperture

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

图/表 12

参考文献 26

相关文章 0

编辑推荐

Metrics

本文评价