文献类型：期刊文献

英文题名：ROBUST ADAPTIVE BEAMFORMING BASED ON PARTICLE FILTER WITH NOISE UNKNOWN

作者：Li, Y.[1];Gu, Y. J.[2];Shi, Z. G.[2];Chen, K. S.[2]

机构：[1]E China Univ Sci & Technol, Dept Elect Engn, Shanghai 200237, Peoples R China;[2]Zhejiang Univ, Dept Elect Engn, Hangzhou 310027, Zhejiang, Peoples R China

年份：2009

卷号：90

起止页码：151

外文期刊名：PROGRESS IN ELECTROMAGNETICS RESEARCH-PIER

收录：;EI(收录号：20091912075452);WOS:【SCI-EXPANDED(收录号:WOS:000265388000011)】；

基金：This work was supported by Natural Science Foundation of China (No.60531020) and Natural Science Foundation of Zhejiang Province (No.Y106384).

语种：英文

外文关键词：Beamforming - Monte Carlo methods - Errors - Bandpass filters - Cost functions - Signal interference - Signal to noise ratio

摘要：Adaptive beamforming, which uses a weight vector to maximize the signal-to-interference-plus-noise ratio (SINR), is often sensitive to estimation error and uncertainty in the parameters, such as direction of arrival (DOA), steering vector and covariance matrix. Robust beamforming attempts to mitigate this sensitivity and diagonal loading in sample covariance matrix can improve the robustness. In this paper, beamformer based on particle filter (PF) is proposed to improve the robustness by optimizing the diagonal loading factor in sample covariance matrix. In the proposed approach, the level of diagonal loading is regarded as a group of particles and optimized using PF. In order to compute the postprobability of particles beyond the knowledge of noise, a simplified cost function is derived first. Then, a statistical approach is developed to decide the level of diagonal loading. Finally, simulations with several frequently encountered types of estimation error are conducted. Results show a better performance of the proposed beamformer than other typical beamformers using diagonal loading. In particular, the prominent advantage of the proposed approach is that it can perform well even noise and error in the steering vector are unknown