@inproceedings{4d99fdce4cc845f19a304ecd045db57c,
title = "Widely linear adaptive beamforming algorithm based on minimum sensitivity and eigenspace",
abstract = "The conventional minimum variance distortionless response (MVDR) beamformer becomes suboptimal for the noncircular signals, and deteriorates when the training samples are limited. The eigenspace-based (ESB) WL MVDR beamformer is proposed, which utilizes the eigenstructure of the correlation matrix to enhance the performance of the WL MVDR beamformer. Further, an eigenspace-based widely linear beamformer for noncircular signals using the minimum sensitivity criterion is proposed, which can be used for reducing the performance degradation when the dimension of the SI subspace can not be estimated correctly. Simulation results show that the proposed method has a better performance.",
keywords = "Adaptive beamforming, MVDR, Minimum sensitivity function, Noncircular signal",
author = "Liping Huo and Xingpeng Mao and Liang Xin and Yunmei Shi and Guangyan Li",
note = "Publisher Copyright: {\textcopyright} Springer Nature Singapore Pte Ltd. 2019.; 6th International Conference on Communications, Signal Processing, and Systems, CSPS 2017 ; Conference date: 14-07-2017 Through 16-07-2017",
year = "2019",
doi = "10.1007/978-981-10-6571-2\_95",
language = "英语",
isbn = "9789811065705",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Verlag",
pages = "782--789",
editor = "Qilian Liang and Min Jia and Jiasong Mu and Wei Wang and Xuhong Feng and Baoju Zhang",
booktitle = "Communications, Signal Processing, and Systems - Proceedings of the 2017 International Conference on Communications, Signal Processing, and Systems",
address = "德国",
}