scholarly journals Fast Angle Estimation and Sensor Self-Calibration in Bistatic MIMO Radar With Gain-Phase Errors and Spatially Colored Noise

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 123701-123710
Author(s):  
Guanqun Sheng ◽  
Han Wang ◽  
Fang-Qing Wen ◽  
Xinhai Wang
Keyword(s):  
Colored Noise ◽  
Mimo Radar ◽  
Angle Estimation ◽  
Bistatic Mimo Radar ◽  
Self Calibration ◽  
Phase Errors

scholarly journals Computationally Efficient Compressed Sensing-Based Method via FG Nyström in Bistatic MIMO Radar with Array Gain-Phase Error Effect

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Jurong Hu ◽  
Evans Baidoo ◽  
Lei Zhan ◽  
Ying Tian
Keyword(s):  
Matching Pursuit ◽  
Phase Error ◽  
Mimo Radar ◽  
Descent Method ◽  
Gradient Descent Method ◽  
Computationally Efficient ◽  
Angle Estimation ◽  
Bistatic Mimo Radar ◽  
Phase Errors ◽  
Sparse Signal Representation

In this paper, a robust angle estimator for uncorrelated targets that employs a compressed sense (CS) scheme following a fast greedy (FG) computation is proposed to achieve improved computational efficiency and performance for the bistatic MIMO radar with unknown gain-phase errors. The algorithm initially avoids the wholly computation of the received signal by compiling a lower approximation through a greedy Nyström approach. Then, the approximated signal is transformed into a sparse signal representation where the sparsity of the target is exploited in the spatial domain. Finally, a CS method, Simultaneous Orthogonal Matching Pursuit with an inherent gradient descent method, is utilized to reconstruct the signal and estimate the angles and the unknown gain-phase errors. The proposed algorithm, aside achieving closed-form resolution for automatically paired angle estimation, offers attractive computational competitiveness, specifically in large array scenarios. Additionally, the analyses of the computational complexity and the Cramér–Rao bounds for angle estimation are derived theoretically. Numerical experiments demonstrate the improvement and effectiveness of the proposed method against existing methods.

scholarly journals New Approach to Angle Estimation for Bistatic MIMO Radar With Unknown Spatially Colored Noise

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 24249-24255 ◽  
Author(s):  
Changxin Cai ◽  
Fangqing Wen ◽  
Dongmei Huang
Keyword(s):  
Colored Noise ◽  
Mimo Radar ◽  
Angle Estimation ◽  
New Approach ◽  
Bistatic Mimo Radar

Angle estimation and mutual coupling self-calibration for ULA-based bistatic MIMO radar

2018 ◽  
Vol 144 ◽  
pp. 61-67 ◽  
Author(s):  
Fangqing Wen ◽  
Zijing Zhang ◽  
Ke Wang ◽  
Guanqun Sheng ◽  
Gong Zhang
Keyword(s):  
Mutual Coupling ◽  
Mimo Radar ◽  
Angle Estimation ◽  
Bistatic Mimo Radar ◽  
Self Calibration

Angle estimation for bistatic MIMO radar in the presence of spatial colored noise

2017 ◽  
Vol 134 ◽  
pp. 261-267 ◽  
Author(s):  
Fangqing Wen ◽  
Xiaodong Xiong ◽  
Jian Su ◽  
Zijing Zhang
Keyword(s):  
Colored Noise ◽  
Mimo Radar ◽  
Angle Estimation ◽  
Bistatic Mimo Radar

Angle Estimation and Self-Calibration Using ISM and ESPRIT for Bistatic MIMO Radar with Gain and Phase Uncertainties

2013 ◽  
Vol 347-350 ◽  
pp. 287-291
Author(s):  
Jian Gong ◽  
Huan Wang ◽  
Zhi Long Li ◽  
Lin Wei
Keyword(s):  
High Resolution ◽  
Mimo Radar ◽  
Angle Estimation ◽  
Bistatic Mimo Radar ◽  
Estimation Algorithms ◽  
Self Calibration ◽  
Simulation Results

Most high-resolution angle estimation algorithms suffer from sensitivity to gain and phase uncertainties. In this letter, a novel ESPRIT-based algorithm, which uses the instrumental sensors method (ISM), is proposed for bistatic MIMO radar with gain and phase uncertainties. With the help of a few well-calibrated transmitting and receiving instrumental sensors, the proposed algorithm is able to achieve favorable and unambiguous angle estimation and accurate self-calibration without the knowledge of gain and phase uncertainties. Simulation results demonstrate the validity of the proposed method.

Sign in / Sign up

Export Citation Format

Share Document