Direction of arrival estimation for the uniform or non-uniform noise with adaptive expectation maximisation algorithm

被引:1
|
作者
Zhang, Fuqiang [1 ]
Zhang, Zenghui [1 ]
Yu, Wenxian [1 ]
机构
[1] Shanghai Jiao Tong Univ, Sch Elect Informat & Elect Engn, Shanghai Key Lab Intelligent Sensing & Recognit, Shanghai, Peoples R China
来源
IET RADAR SONAR AND NAVIGATION | 2020年 / 14卷 / 07期
基金
中国国家自然科学基金;
关键词
direction-of-arrival estimation; passive radar; iterative methods; expectation-maximisation algorithm; adaptive expectation maximisation algorithm; signal component; DOA estimation performance; initial noise power ratio; AEM algorithm; uniform noise estimation; nonuniform noise estimation; NUN estimation; UN estimation; passive radar waveform estimation; LIKELIHOOD DOA ESTIMATION; MAXIMUM-LIKELIHOOD; CORRELATED NOISE; EM; LOCALIZATION; SIGNALS;
D O I
10.1049/iet-rsn.2019.0584
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The authors consider the problem of direction-of-arrival (DOA) estimation for the uniform noise (UN) or non-UN (NUN) in a passive radar. The radar waveform to be estimated is modelled as a deterministic and unknown process. Under this condition, the well-known expectation maximisation (EM) algorithm can be utilised for the estimation. In the conventional EM algorithm, the DOA is updated in every iteration, whereas the noise power ratio for each signal component is kept constant. Hence, they have to specify the noise power ratio before implementing the EM algorithm. Clearly, the DOA estimation performance of the conventional EM algorithm is sensitive to this initial noise power ratio. To deal with this problem, they propose the adaptive EM (AEM) algorithms for the UN and NUN, respectively. In the authors' proposed AEM algorithm, the noise power and DOA are jointly estimated and updated in each iteration, which indicates that the noise power ratio for each signal component would be adaptively changed. Therefore, the DOA performance of their proposed AEM algorithm is less sensitive to the initial noise power ratio, thereby achieving better estimation results. Finally, extensive experiments are carried out to validate the effectiveness of their proposed AEM algorithm.
引用
收藏
页码:1029 / 1038
页数:10
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