Maximum likelihood DOA estimator based on importance sampling

Jianguo Huang, Da Xie, Xiong Li, Qunfei Zhang

科研成果: 书/报告/会议事项章节会议稿件同行评审

1 引用 (Scopus)

摘要

DOA estimation is an important research area in array signal processing. Maximum Likelihood Estimator (MLE) has been shown to perform best among all the methods. However, the MLE requires a multidimensional grid search and the computational burden increases exponentially with the dimension. So it is difficult to be used in realtime applications. In order to reduce the computation, Monte Carlo methods are combined with MLE. A novel Maximum Likelihood DOA Estimator based on Importance Sampling (ISMLE) is proposed. ISMLE not only reduces the computational complexity of the original MLE from O(LK) to O(KXH), but also keeps the perfect original performance of the MLE. Simulation results show that ISMLE keeps the excellent performance of MLE, and simultaneously it reduces the computation obviously. Also ISMLE performs better than MUSIC and MiniNorm, especially in low SNRs.

源语言英语
主期刊名2006 IEEE Region 10 Conference, TENCON 2006
出版商Institute of Electrical and Electronics Engineers Inc.
ISBN(印刷版)1424405491, 9781424405497
DOI
出版状态已出版 - 2006
活动2006 IEEE Region 10 Conference, TENCON 2006 - Hong Kong, 中国
期限: 14 11月 200617 11月 2006

出版系列

姓名IEEE Region 10 Annual International Conference, Proceedings/TENCON
ISSN(印刷版)2159-3442
ISSN(电子版)2159-3450

会议

会议2006 IEEE Region 10 Conference, TENCON 2006
国家/地区中国
Hong Kong
时期14/11/0617/11/06

指纹

探究 'Maximum likelihood DOA estimator based on importance sampling' 的科研主题。它们共同构成独一无二的指纹。

引用此