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Journal ArticleDOI

Middle Subarray Interference Covariance Matrix Reconstruction Approach for Robust Adaptive Beamforming With Mutual Coupling

Zhihui Li, +3 more
- 15 Feb 2019 - 
- Vol. 23, Iss: 4, pp 664-667
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TLDR
A middle subarray interference-plus-noise covariance matrix (INCM) reconstruction approach is proposed to mitigate the mutual coupling problem in robust adaptive beamforming and simulation results validate the superiority and effectiveness of the proposed method.
Abstract
In this letter, a middle subarray interference-plus-noise covariance matrix (INCM) reconstruction approach is proposed to mitigate the mutual coupling problem in robust adaptive beamforming. In the proposed approach, the banded symmetric Toeplitz structure of mutual coupling matrix in the uniform linear array is employed. The INCM of middle subarray is first reconstructed by using the Capon spectrum of middle subarray to integrate over the possible interference region. Similarly, the desired signal covariance matrix of middle array is calculated over the desired signal region, and the desired signal steering vector of middle array is estimated. Finally, the proposed middle subarray beamformer weight vector is obtained. Simulation results validate the superiority and effectiveness of the proposed method.

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Citations
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Journal ArticleDOI

An RCB-Like Steering Vector Estimation Method Based on Interference Matrix Reduction

TL;DR: This article designs an SOI power estimator to formulate the steering vector optimization problem with an uncertainty set constraint and shows that the proposed approach can outperform the compared ones with reduced complexity in the situation of various steering vector mismatches.
Journal ArticleDOI

Adaptive Beamforming via Desired Signal Robust Removal for Interference-Plus-Noise Covariance Matrix Reconstruction

TL;DR: A robust interference-plus-noise covariance matrix (INCM) reconstruction method based upon DS removal is presented and the proposed adaptive beamformer can outperform the existing ones and gain almost optimal performance under different scenarios.
Journal ArticleDOI

A Robust Capon Beamforming Approach for Sparse Array Based on Importance Resampling Compressive Covariance Sensing

TL;DR: The robust beamforming with the importance resampling based compressive covariance sensing is proposed, which is shown to outperform the classical beamforming method based on reconstructing the interference-plus-noise covariance matrix.
Journal ArticleDOI

Robust and Efficient Adaptive Beamforming Using Nested Subarray Principles

TL;DR: An adaptive beamforming algorithm for large uniform linear arrays (ULAs), where only a nested subarray is utilized to calculate the beamforming coefficients for the original ULA, which fundamentally eliminates the SOI component.
References
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Journal ArticleDOI

Robust adaptive beamforming using worst-case performance optimization: a solution to the signal mismatch problem

TL;DR: A new approach to robust adaptive beamforming in the presence of an arbitrary unknown signal steering vector mismatch is developed based on the optimization of worst-case performance.
Journal ArticleDOI

On robust Capon beamforming and diagonal loading

TL;DR: It is shown that a natural extension of the Capon beamformer to the case of uncertain steering vectors also belongs to the class of diagonal loading approaches, but the amount of diagonalloading can be precisely calculated based on the uncertainty set of the steering vector.
Proceedings ArticleDOI

On robust Capon beamforming and diagonal loading

TL;DR: This paper shows that a natural extension of the Capon beamformer to the case of uncertain steering vectors also belongs to the class of diagonal loading approaches but the amount of diagonalloading can be precisely calculated based on the uncertainty set of the steering vector.
Journal ArticleDOI

Robust Adaptive Beamforming Based on Interference Covariance Matrix Reconstruction and Steering Vector Estimation

TL;DR: Simulation results demonstrate that the performance of the proposed adaptive beamforming algorithm is almost always close to the optimal value across a wide range of signal to noise and signal to interference ratios.
Journal ArticleDOI

A Robust and Efficient Algorithm for Coprime Array Adaptive Beamforming

TL;DR: This paper decomposes the coprime array into a pair of sparse uniform linear subarrays and process their received signals separately, and proposes a novel coprimes array adaptive beamforming algorithm, where both robustness and efficiency are well balanced.
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