2-Dimensional Arrival Angle Estimation and Self-calibration Algorithm for L-shaped Array in the Presence of Mutual Coupling

2011 ◽  
Author(s):  
Hu Xiaoqin ◽  
Wang Yongliang ◽  
Chen Hui
Keyword(s):  
Mutual Coupling ◽  
Arrival Angle ◽  
Angle Estimation ◽  
Self Calibration ◽  
Calibration Algorithm

scholarly journals Angle Estimation and Mutual Coupling Self-Calibration in Bistatic MIMO System with Arbitrary Geometry

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Tingping Zhang ◽  
Di Wan ◽  
Xinhai Wang ◽  
Fangqing Wen
Keyword(s):  
Mutual Coupling ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Property A ◽  
Angle Estimation ◽  
Self Calibration ◽  
Direction Of Departure ◽  
Input Multiple Output ◽  
Uniform Array ◽  
Sensor Geometry

Ideal array responses are often desirable to a multiple-input multiple-output (MIMO) system. Unfortunately, it may not be guaranteed in practice as the mutual coupling (MC) effects always exist. Current works concerning MC in the MIMO system only account for the uniform array geometry scenario. In this paper, we generalize the issue of angle estimation and MC self-calibration in a bistatic MIMO system in the case of arbitrary sensor geometry. The MC effects corresponding to the transmit array and the receive array are modeled by two MC matrices with several distinct entities. Angle estimation is then recast to a linear constrained quadratic problem. Inspired by the MC transformation property, a multiple signal classification- (MUSIC-) like strategy is proposed, which can estimate the direction-of-departure (DOD) and direction-of-arrival (DOA) via two individual spectrum searches. Thereafter, the MC coefficients are obtained by exploiting the orthogonality between the signal subspace and the noise subspace. The proposed method is suitable for arbitrary sensor geometry. Detailed analyses with respect to computational complexity, identifiability, and Cramer-Rao bounds (CRBs) are provided. Simulation results validate the effectiveness of the proposed method.

scholarly journals A Novel Self-Calibration Method for Acoustic Vector Sensor

2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Yao Zhang ◽  
Jin Fu ◽  
Guannan Li
Keyword(s):  
Acoustic Pressure ◽  
Calibration Method ◽  
Estimation Accuracy ◽  
Spatial Gradient ◽  
Arrival Angle ◽  
Acoustic Vector Sensor ◽  
Self Calibration ◽  
Vector Sensor ◽  
Calibration Algorithm ◽  
Simulation Results

The acoustic vector sensor (AVS) can measure the acoustic pressure field’s spatial gradient, so it has directionality. But its channels may have nonideal gain/phase responses, which will severely degrade its performance in finding source direction. To solve this problem, in this study, a self-calibration algorithm based on all-phase FFT spectrum analysis is proposed. This method is “self-calibrated” because prior knowledge of the training signal’s arrival angle is not required. By measuring signals from different directions, the initial phase can be achieved by taking the all-phase FFT transform to each channel. We use the amplitude of the main spectrum peak of every channel in different direction to formulate an equation; the amplitude gain estimates can be achieved by solving this equation. In order to get better estimation accuracy, bearing difference of different training signals should be larger than a threshold, which is related to SNR. Finally, the reference signal’s direction of arrival can be estimated. This method is easy to implement and has advantage in accuracy and antinoise. The efficacy of this proposed scheme is verified with simulation results.

A self-calibration algorithm for cross array in the presence of mutual coupling

2010 ◽  
Vol 54 (4) ◽  
pp. 836-848 ◽  
Author(s):  
XiaoQin Hu ◽  
Hui Chen ◽  
YongLiang Wang ◽  
JianWen Chen
Keyword(s):  
Mutual Coupling ◽  
Self Calibration ◽  
Calibration Algorithm

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
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