High-Precision Mutual Coupling Coefficient Estimation for Adaptive Beamforming

Ziang Feng,Guoping Hu,Hao Zhou,Qichao Ge,Liangtian Wan

doi:10.1155/2020/6669547

Abstract

Here, a high-precision mutual coupling coefficient estimation method is proposed that is more suitable for adaptive beamforming than traditional algorithms. According to the relationship between the designed transition matrix and the signal, the proposed algorithm selects the transition matrix corresponding to the high-power signal. The high-precision estimation of the mutual coupling coefficient is obtained by using the selected transition matrix estimation, which yields relatively good estimation accuracy for the mutual coupling coefficient when the desired signal-to-noise ratio (SNR) is low and relatively robust adaptive beamforming with unknown mutual coupling. Simulation results demonstrate the validity of the proposed method.

Highlights

Signal processing technology, such as direction of arrival (DOA) and robust adaptive beamforming (RAB), has been widely used in radar, sonar, communication, etc. [1,2,3,4,5,6,7]
An iterative autocalibration algorithm based on the eigendecomposition of the sampling covariance matrix for a uniform circular array (UCA) is proposed to calibrate unknown mutual coupling since the mutual coupling matrix (MCM) has a complex symmetric circular Toeplitz structure in a UCA in [16]
The middle subarray-based (MSB) approach reduces the degree of freedom (DOF) of the array, and the complex structure of the maximum interelement spacing constraint (MISC) array increases the difficulty of signal processing, while the subspace-based method in [14] constructs a high-dimensional matrix, and the algorithms proposed in [16, 18] both need an iterative process

Summary

Introduction

Signal processing technology, such as direction of arrival (DOA) and robust adaptive beamforming (RAB), has been widely used in radar, sonar, communication, etc. [1,2,3,4,5,6,7]. To avoid the influence of mutual coupling, a middle subarray-based (MSB) approach is proposed in [12], and a maximum interelement spacing constraint (MISC) array is designed in [13]. An iterative autocalibration algorithm based on the eigendecomposition of the sampling covariance matrix for a uniform circular array (UCA) is proposed to calibrate unknown mutual coupling since the MCM has a complex symmetric circular Toeplitz structure in a UCA in [16]. To improve the robustness of adaptive beamforming in the presence of unknown mutual coupling, a middle subarray-plus-reconstruction-based (MSRB) method combining the MSB algorithm with interference-plus-noise covariance matrix (INCM) reconstruction [21] is proposed in [22]. The designed beamformer is more robust than the existing beamformer to mutual coupling

Signal Mode

Proposed Algorithm

Simulations

Findings

Conclusion