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: 6582
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.
@article{title="Joint compressed sensing imaging and phase adjustment via an iterative method for multistatic passive radar",
author="Jue Wang, Jun Wang",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="19",
number="4",
pages="557-568",
year="2018",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1601423"
}
%0 Journal Article
%T Joint compressed sensing imaging and phase adjustment via an iterative method for multistatic passive radar
%A Jue Wang
%A Jun Wang
%J Frontiers of Information Technology & Electronic Engineering
%V 19
%N 4
%P 557-568
%@ 2095-9184
%D 2018
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1601423
TY - JOUR
T1 - Joint compressed sensing imaging and phase adjustment via an iterative method for multistatic passive radar
A1 - Jue Wang
A1 - Jun Wang
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 19
IS - 4
SP - 557
EP - 568
%@ 2095-9184
Y1 - 2018
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.1601423
Abstract: 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.
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