Airborne sparse flight array SAR 3D imaging based on compressed sensing in frequency domain

doi:10.23919/JSEE.2022.000125

Abstract

Abstract:

In airborne array synthetic aperture radar (SAR), the three-dimensional (3D) imaging performance and cross-track resolution depends on the length of the equivalent array. In this paper, Barker sequence criterion is used for sparse flight sampling of airborne array SAR, in order to obtain high cross-track resolution in as few times of flights as possible. Under each flight, the imaging algorithm of back projection (BP) and the data extraction method based on modified uniformly redundant arrays (MURAs) are utilized to obtain complex 3D image pairs. To solve the side-lobe noise in images, the interferometry between each image pair is implemented, and compressed sensing (CS) reconstruction is adopted in the frequency domain. Furthermore, to restore the geometrical relationship between each flight, the phase information corresponding to negative MURA is compensated on each single-pass image reconstructed by CS. Finally, by coherent accumulation of each complex image, the high resolution in cross-track direction is obtained. Simulations and experiments in X-band verify the availability.

Key words: three-dimensional (3D) imaging, synthetic aperture radar (SAR), sparse flight, interferometry, compressed sensing (CS)

He TIAN, Chunzhu DONG, Hongcheng YIN, Li YUAN. Airborne sparse flight array SAR 3D imaging based on compressed sensing in frequency domain[J]. Journal of Systems Engineering and Electronics, 2023, 34(1): 56-67.

Figures/Tables 19

Fig 1

Fig 2

Fig 3

Fig 4

Table 1

Fig 5

Fig 6

Fig 7

Fig 8

Fig 9

Fig 10

Fig 11

Fig 12

Table 2

Fig 13

Table 3

Fig 14

Fig 15

Table 4

References 29

2	GOLOMB S, SCHOLTZ R Generalized barker sequences. IEEE Trans. on Information Theory, 1965, 11 (4): 533- 537. doi: 10.1109/TIT.1965.1053828
3	HOLUBNYCHYI A. Generalized binary barker sequences and their application to radar technology. Proc. of the Signal Processing Symposium, 2013. DOI: 10.1109/SPS.2013.6623610.
4	SKOLNIK M I. Radar handbook. 3rd ed. Beijing: Publishing House of Electronics Industry, 2003.
5	LI D J, TENG X M Cross-track spare flight simulation analysis for airborn sparse array downward-looking 3D imaging radar. Proc. of the Geoscience and Remote Sensing Symposium, 2011, 1686- 1688.
6	TIAN H, LI D J, LI L C Simulation of signal reconstruction based sparse flight downward looking 3D imaging SAR. Proc. of the Geoscience and Remote Sensing Symposium, 2015, 3762- 3765.
7	LI L C, LI D J, PAN Z H Compressed sensing application in interferometric synthetic aperture radar. Science China Information Sciences, 2017, 60 (10): 102305. doi: 10.1007/s11432-016-9017-6
8	TIAN H, LI D J Sparse flight array SAR downward-looking 3-D imaging based on compressed sensing. IEEE Geoscience and Remote Sensing Letters, 2016, 13 (10): 1395- 1399. doi: 10.1109/LGRS.2016.2560238
9	CANDES E J, ROMBERG J Sparsity and incoherence in compressive sampling. Inverse Problems, 2007, 23 (3): 969- 985. doi: 10.1088/0266-5611/23/3/008
10	DONOHO D L Compressed sensing. IEEE Trans. on Information Theory, 2006, 52 (4): 1289- 1306. doi: 10.1109/TIT.2006.871582
11	CANDES E J, WAKIN M B An introduction to compressive sampling. IEEE Signal Processing Magazine, 2008, 25 (2): 21- 30. doi: 10.1109/MSP.2007.914731
12	BARANIUK R, STEEGHS P Compressive radar imaging. Proc. of the IEEE Radar Conference, 2007, 128- 133.
13	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
14	LI D J, TENG X M, PAN Z H The concept and applications of distributed POS. Journal of Radars, 2013, 2 (4): 400- 405.
1	WILEY C A Synthetic aperture radars. IEEE Trans. on Aerospace and Electronic Systems, 1985, 21 (3): 440- 443.
15	YE W, LI J L, LI L C Design and development of a real-time multi-DSPS and FPGA-based DPOS for InSAR applications. IEEE Sensors Journal, 2018, 18 (8): 3419- 3425. doi: 10.1109/JSEN.2018.2799622
16	PETERMAN D, JAMES K, GLAVAC V. Distortion measurement and compensation in a synthetic aperture radar phased-array antenna. Proc. of the 14th International Symposium on Antenna Technology and Applied Electromagnetics the American Electromagnetics Conference, 2010. DOI:10.1109/ANTEM.2010.5552555.
17	CUMMING I G, WONG F H. Digital processing of synthetic aperture radar data: algorithms and implementation. Norwood: Artech House, 2005.
18	TIAN H, LI D J, PAN J Downward-looking 3D imaging processing of sparse array SAR based on MURA positive and negative coding. Journal of Electronics and Information Technology, 2017, 39 (9): 2203- 2211.
19	TIAN H, LI D J, HU X Microwave three-dimensional imaging under sparse sampling based on MURA code. Proc. of the IEEE International Geoscience and Remote Sensing Symposium, 2016, 7411- 7414.
20	ULANDER L, HELLSTEN H, STENSTROM G Synthetic-aperture radar processing using fast factorized back-projection. IEEE Trans. on Aerospace and Electronic Systems, 2003, 39 (3): 760- 776. doi: 10.1109/TAES.2003.1238734
21	FARHAT N H, WERNER C L, CHU T H Prospects for three-dimensional projective and tomographic imaging radar networks. Radio Science, 1984, 19 (5): 1347- 1355. doi: 10.1029/RS019i005p01347
22	GIERULL C H On a concept for an airborne downward-looking imaging radar. AEU International Journal of Electronics and Communications, 1999, 53 (6): 295- 304.
23	TIAN H, DONG C Z, SHENG J, et al Motion compensation and 3-D imaging algorithm in sparse flight based airborne array SAR. Procedia Computer Science, 2021, (187): 464- 473.
24	ROSEN P A, HENSLEY S, JOUGHIN I R, et al Synthetic aperture radar interferometry. Proceedings of the IEEE, 2000, 88 (3): 333- 382. doi: 10.1109/5.838084
25	SAMADI S, CETIN M, MASNADI-SHIRAZI M A Sparse representation-based synthetic aperture radar imaging. IET Radar, Sonar & Navigation, 2011, 5 (2): 182- 193. doi: 10.1049/iet-rsn.2009.0235
26	FENIMORE E E, CANNON T M A class of near-perfect coded apertures. IEEE Trans. on Nuclear Science, 1978, 25 (1): 184- 188. doi: 10.1109/TNS.1978.4329301
27	TIAN H, LI D J. Sparse sampling-based microwave 3D imaging using interferometry and frequency-domain principal component analysis. IET Radar, Sonar & Navigation, 2017, 11(12): 1886–1891.
28	SAMADI S, SHAMSOLLAHI M B. ECG noise reduction using empirical mode decomposition based on combination of instantaneous half period and soft-thresholding. Proc. of the 2nd Middle East Conference on Biomedical Engineering, 2014: 244−248.
29	SHANABLEH T Prediction of structural similarity index of compressed video at a macroblock level. IEEE Signal Processing Letters, 2011, 18 (5): 335- 338. doi: 10.1109/LSP.2011.2130524

Parameter	Value
Platform height/m	2 000
Band width/MHz	300
Working wavelength/m	0.03
Pulse repeat frequency/Hz	400
Interval length of equivalent phase centers/m	0.15
Number equivalent phase centers	65
Antenna width in the cross-track direction/m	200
Along-track antenna size/m	1.00
Cross-track length of antenna array/m	9.00
Interval length between each flight track/m	9.15
Resolution in the along-track direction/m	0.50
Resolution in altitude direction/m	0.50
Resolution in the cross-track direction with single flight/m	3.33
Resolution in cross-track direction with seven flights/m	0.47
Resolution in the cross-track direction with four sparse flights/m	0.55

Imaging method	Correlation coefficient	RMSE/m	SSIM
DI, single flight, ideal motion	0.737 8	0.108 3	0.793 6
DI, complete flight (seven times), ideal motion	0.921 6	0.011 1	0.953 2
DI, sparse flight, non-ideal motion	0.820 5	0.027 6	0.890 8
ICS, sparse flight, non-ideal motion	0.890 4	0.015 1	0.931 2

Parameter	Value
Measuring distance/m	1.60
Working wavelength/m	0.03
System bandwidth/GHz	4
Sampling number in the along-track direction	51
Sampling number in the cross-track direction	51
Sampling number in the altitude direction	201
Size of sampling plane/(m×m)	1.00×1.00
Resolution in the along-track direction/m	0.027
Resolution in the cross-track direction/m	0.027
Resolution in the range direction/m	0.0375

Imaging method	Correlation coefficient	RMSE/m	SSIM
DI, sparse sampling	0.875 9	0.010 4	0.953 5
DI, sparse sampling	0.832 9	0.020 4	0.913 3
ICS, sparse sampling	0.878 1	0.011 5	0.964 7

[1]	Xiuli KOU, Guanyong WANG, Jun LI, Jie CHEN. Coherent change detection of fine traces based on multi-angle SAR observations [J]. Journal of Systems Engineering and Electronics, 2023, 34(1): 1-8.
[2]	Man ZHANG, Guanyong WANG, Feiming WEI, Xue JIN. Coherent range-dependent map-drift algorithm for improving SAR motion compensation [J]. Journal of Systems Engineering and Electronics, 2023, 34(1): 47-55.
[3]	Hao FENG, Jianzhong WU, Lu ZHANG, Mingsheng LIAO. Unsupervised change detection of man-made objects using coherent and incoherent features of multi-temporal SAR images [J]. Journal of Systems Engineering and Electronics, 2022, 33(4): 896-906.
[4]	Hao ZHANG, Bin CUI, Zhichao GUAN, Han DUN. Comparison of density and positioning accuracy of PS extracted from super-resolution PSI with those from traditional PSI [J]. Journal of Systems Engineering and Electronics, 2021, 32(6): 1318-1324.
[5]	Junqiu ZHANG, Yong WANG, Xiaofei LU. Distributed inverse synthetic aperture radar imaging of ship target with complex motion [J]. Journal of Systems Engineering and Electronics, 2021, 32(6): 1325-1337.
[6]	Ruifeng FAN, Xunhe YIN, Zhenfei LIU, Hak Keung LAM. Compensated methods for networked control system with packet drops based on compressed sensing [J]. Journal of Systems Engineering and Electronics, 2021, 32(6): 1539-1556.
[7]	Kai ZHOU, Daojing LI, Anjing CUI, Dong HAN, He TIAN, Haifeng YU, Jianbo DU, Lei LIU, Yu ZHU, Running ZHANG. Sparse flight spotlight mode 3-D imaging of spaceborne SAR based on sparse spectrum and principal component analysis [J]. Journal of Systems Engineering and Electronics, 2021, 32(5): 1143-1151.
[8]	Xuying XIONG, Gen LI, Yanheng MA, Lina CHU. New slant range model and azimuth perturbation resampling based high-squint maneuvering platform SAR imaging [J]. Journal of Systems Engineering and Electronics, 2021, 32(3): 545-558.
[9]	Xiangyang LIU, Bingpeng ZHANG, Wei CAO, Wenjia XIE. Sparse three-dimensional imaging for forward-looking array SAR using spatial continuity [J]. Journal of Systems Engineering and Electronics, 2021, 32(2): 417-424.
[10]	Yuhan LI, Wei QI, Zhenmiao DENG, Maozhong FU, Yunjian ZHANG. Monopulse instantaneous 3D imaging for wideband radar system [J]. Journal of Systems Engineering and Electronics, 2021, 32(1): 53-67.
[11]	Jing FANG, Shaohai HU, Xiaole MA. SAR image de-noising via grouping-based PCA and guided filter [J]. Journal of Systems Engineering and Electronics, 2021, 32(1): 81-91.
[12]	Wensheng CHANG, Haihong TAO, Yanbin LIU, Guangcai SUN. Design of synthetic aperture radar low-intercept radio frequency stealth [J]. Journal of Systems Engineering and Electronics, 2020, 31(1): 64-72.
[13]	Shuzhen WANG, Yang FANG, Jin'gang ZHANG, Mingshi LUO, Qing LI. Near-field 3D imaging approach combining MJSR and FGG-NUFFT [J]. Journal of Systems Engineering and Electronics, 2019, 30(6): 1096-1109.
[14]	Jiansheng HU, Zuxun SONG, Shuxia GUO, Qian ZHANG, Dongdong SHUI. Sparse channel recovery with inter-carrier interference self-cancellation in OFDM [J]. Journal of Systems Engineering and Electronics, 2018, 29(4): 676-683.
[15]	Chun LIU, Chunhua XIE, Jian YANG, Yingying XIAO, Junliang BAO. A method for coastal oil tank detection in polarimetric SAR images based on recognition of T-shaped harbor [J]. Journal of Systems Engineering and Electronics, 2018, 29(3): 499-509.