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CLC number: TN95

On-line Access: 2018-06-07

Received: 2016-09-13

Revision Accepted: 2017-01-23

Crosschecked: 2018-04-12

Cited: 0

Clicked: 6073

Citations:  Bibtex RefMan EndNote GB/T7714


Jun Wang


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Frontiers of Information Technology & Electronic Engineering  2018 Vol.19 No.4 P.557-568


Joint compressed sensing imaging and phase adjustment via an iterative method for multistatic passive radar

Author(s):  Jue Wang, Jun Wang

Affiliation(s):  National Laboratory of Radar Signal Processing, Xidian University, Xian 710071, China

Corresponding email(s):   xdwangjue@163.com

Key Words:  Multistatic passive radar, Compressed sensing, Phase adjustment, Fixed-point iteration technique

Jue Wang, Jun Wang. Joint compressed sensing imaging and phase adjustment via an iterative method for multistatic passive radar[J]. Frontiers of Information Technology & Electronic Engineering, 2018, 19(4): 557-568.

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The resolution of the multistatic passive radar imaging system (MPRIS) is poor due to the narrow bandwidth of the signal transmitted by illuminators of opportunity. Moreover, the inaccuracies caused by the inaccurate tracking system or the error position measurement of illuminators or receivers can deteriorate the quality of an image. To improve the performance of an MPRIS, an imaging method based on the tomographic imaging principle is presented. Then the compressed sensing technique is extended to the MPRIS to realize high-resolution imaging. Furthermore, a phase correction technique is developed for compensating for phase errors in an MPRIS. Phase errors can be estimated by iteratively solving an equation that is derived by minimizing the mean recovery error of the reconstructed image based on the principle of fixed-point iteration technique. The technique is nonparametric and can be used to estimate phase errors of any form. The effectiveness and convergence of the technique are confirmed by numerical simulations.




Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


[1]Berizzi F, Corsini G, 1996. Autofocusing of inverse synthetic aperture radar images using contrast optimization. IEEE Trans Aerosp Electron Syst, 32(3):1185-1191.

[2]Berizzi F, Martorella M, Haywood B, et al., 2004. A survey on ISAR autofocusing techniques. Proc Int Conf on Image Processing, p.9-12.

[3]Brisken S, Martella M, 2014. Multistatic ISAR autofocus with an image entropy-based technique. IEEE Aerosp Electron Syst Mag, 29(7):30-36.

[4]Brisken S, Martorella M, Mathy T, et al., 2012. Multistatic ISAR autofocussing using image contrast optimization. IET Int Conf on Radar Systems, p.1-4.

[5]Brisken S, Martorella M, Mathy T, et al., 2014. Motion estimation and imaging with a multistatic ISAR system. IEEE Trans Aerosp Electron Syst, 50(3):1701-1714.

[6]Candès EJ, Tao T, 2006. Near-optimal signal recovery from random projections: universal encoding strategies? IEEE Trans Inform Theory, 52(12):5406-5425.

[7]Donoho DL, 2006. Compressed sensing. IEEE Trans Inform Theory, 52(4):1289-1306.

[8]Giusti E, Tomei S, Bacci A, et al., 2013. Autofocus for CS based ISAR imaging in the presence of gapped data. Proc 2nd Int Workshop on Compressed Sensing Applied to Radar, p.1-4.

[9]Gonzalez-Valdes B, Allan G, Rodriguez-Vaqueiro Y, et al., 2014. Sparse array optimization using simulated annealing and compressed sensing for near-field millimeter wave imaging. IEEE Trans Antennas Propag, 62(4): 1716-1722.

[10]Grant M, 2010. CVX: Matlab Software for Disciplined Convex Programming, Version 1.21. http://cvxr.com/cvx

[11]Kirsch A, 2011. An Introduction to the Mathematical Theory of Inverse Problems. Springer Science & Business Media, New York, NY.

[12]Liu J, Li HB, Himed B, 2014. Two target detection algorithms for passive multistatic radar. IEEE Trans Signal Process, 62(22):5930-5939.

[13]Lv XY, Wang J, Wang J, 2015. Robust direction of arrival estimate method in FM-based passive bistatic radar with a four-element Adcock antenna array. IET Radar Sonar Navig, 9(4):392-400.

[14]Mensa D, Heidbreder G, Wade G, 1980. Aperture synthesis by object rotation in coherent imaging. IEEE Trans Nucl Sci, 27(2):989-998.

[15]Önhon NÖ, Çetin M, 2012. A sparsity-driven approach for joint SAR imaging and phase error correction. IEEE Trans Image Process, 21(4):2075-2088.

[16]Stojanovic I, Çetin M, Karl WC, 2013. Compressed sensing of monostatic and multistatic SAR. IEEE Geosci Remote Sens Lett, 10(6):1444-1448.

[17]Wang J, Liu X, Zhou Z, 2004. Minimum-entropy phase adjustment for ISAR. IEE Proc Radar Sonar Navig, 151(4):203-209.

[18]Wang J, Zhang XW, Bao Z, 2006. Passive radar imaging algorithm based on sub-apertures synthesis of multiple television stations. Proc Int Conf on Radar, p.1-4.

[19]Wu QS, Zhang YD, Amin MG, et al., 2015. High-resolution passive SAR imaging exploiting structured Bayesian compressive sensing. IEEE J Sel Top Signal Process, 9(8):1484-1497.

[20]Yarman CE, Wang L, Yazici B, 2010. Passive synthetic aperture radar imaging with single frequency sources of opportunity. Proc IEEE Radar Conf, p.949-954.

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