基于迭代梯度方法的线性约束稳健Capon波束形成快速算法

Translated title of the contribution: A Fast Algorithm for Linear Constrained Robust Capon Beamforming Based on Iterative Gradient Method

Xiangyu Guo, Shefeng Yan, Wenxia Wang

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

In order to reduce the amount of calculation of the linearly constrained robust adaptive beamforming algorithm, so that it could be applied to the real-time signal processing application scenarios of single-snapshot updating, this paper proposed a fast algorithm for linearly constrained robust Capon beamforming (LCRCB) based on single-snap shot updating and iterative gradient method, with the time complexity optimized from 0(M3) to 0(M2). The algorithm used rank-1 updating to maintain the required inverse matrix, calculated the linear constraint part of the weight, and used the iterative gradient method to update the adaptive part of the weight. The two parts are scaled and added according to the constraint to obtain the weight. Numerical simulation shows that the algorithm converges quickly and has almost the same performance as the original LCRCB.

Translated title of the contributionA Fast Algorithm for Linear Constrained Robust Capon Beamforming Based on Iterative Gradient Method
Original languageChinese (Traditional)
Pages (from-to)712-723
Number of pages12
JournalJournal of Signal Processing
Volume37
Issue number5
DOIs
Publication statusPublished - May 2021
Externally publishedYes

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