A Compressive Sensing-Based Bistatic MIMO Radar Imaging Method in the Presence of Array Errors

A robust transmit-receive angle imaging method for bistatic MIMO radar based on compressed sensing is proposed. A new imaging model with array gain and phase error is established. The array gain error and phase error were modeled as a random interference for observation matrix by mathematical deriva...

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Main Authors: Zhigang Liu, Jun Li, Junqing Chang, Yifan Guo
Format: Article
Language:English
Published: Wiley 2018-01-01
Series:International Journal of Antennas and Propagation
Online Access:http://dx.doi.org/10.1155/2018/9434360
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author Zhigang Liu
Jun Li
Junqing Chang
Yifan Guo
author_facet Zhigang Liu
Jun Li
Junqing Chang
Yifan Guo
author_sort Zhigang Liu
collection DOAJ
description A robust transmit-receive angle imaging method for bistatic MIMO radar based on compressed sensing is proposed. A new imaging model with array gain and phase error is established. The array gain error and phase error were modeled as a random interference for observation matrix by mathematical derivation. A constraint of observation matrix error is constructed in optimization problem of sparse recovery to reduce the effect of the interference of observation matrix. Then, the iterative algorithm of the optimization problems is derived. The proposed recovery method is more robust than the existed method in small samples, especially in the case of one snapshot. It is applicable in the case of relatively small array gain and phase errors. Simulation results confirm the effectiveness of the proposed method.
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publishDate 2018-01-01
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series International Journal of Antennas and Propagation
spelling doaj-art-99133e69abe844789b3a8f8c69f5983e2025-08-20T03:37:05ZengWileyInternational Journal of Antennas and Propagation1687-58691687-58772018-01-01201810.1155/2018/94343609434360A Compressive Sensing-Based Bistatic MIMO Radar Imaging Method in the Presence of Array ErrorsZhigang Liu0Jun Li1Junqing Chang2Yifan Guo3National Lab of Radar Signal Processing, Xidian University, Xi’an 710071, ChinaNational Lab of Radar Signal Processing, Xidian University, Xi’an 710071, ChinaNational Lab of Radar Signal Processing, Xidian University, Xi’an 710071, ChinaNational Lab of Radar Signal Processing, Xidian University, Xi’an 710071, ChinaA robust transmit-receive angle imaging method for bistatic MIMO radar based on compressed sensing is proposed. A new imaging model with array gain and phase error is established. The array gain error and phase error were modeled as a random interference for observation matrix by mathematical derivation. A constraint of observation matrix error is constructed in optimization problem of sparse recovery to reduce the effect of the interference of observation matrix. Then, the iterative algorithm of the optimization problems is derived. The proposed recovery method is more robust than the existed method in small samples, especially in the case of one snapshot. It is applicable in the case of relatively small array gain and phase errors. Simulation results confirm the effectiveness of the proposed method.http://dx.doi.org/10.1155/2018/9434360
spellingShingle Zhigang Liu
Jun Li
Junqing Chang
Yifan Guo
A Compressive Sensing-Based Bistatic MIMO Radar Imaging Method in the Presence of Array Errors
International Journal of Antennas and Propagation
title A Compressive Sensing-Based Bistatic MIMO Radar Imaging Method in the Presence of Array Errors
title_full A Compressive Sensing-Based Bistatic MIMO Radar Imaging Method in the Presence of Array Errors
title_fullStr A Compressive Sensing-Based Bistatic MIMO Radar Imaging Method in the Presence of Array Errors
title_full_unstemmed A Compressive Sensing-Based Bistatic MIMO Radar Imaging Method in the Presence of Array Errors
title_short A Compressive Sensing-Based Bistatic MIMO Radar Imaging Method in the Presence of Array Errors
title_sort compressive sensing based bistatic mimo radar imaging method in the presence of array errors
url http://dx.doi.org/10.1155/2018/9434360
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