Robust DOA Estimation in the Presence of Miscalibrated Sensors

被引:37
作者
Wang, Ben [1 ,2 ]
Zhang, Yimin D. [2 ]
Wang, Wei [1 ]
机构
[1] Harbin Engn Univ, Coll Automat, Harbin 150001, Peoples R China
[2] Temple Univ, Dept Elect & Comp Engn, Philadelphia, PA 19122 USA
基金
美国国家科学基金会; 中国博士后科学基金;
关键词
Calibration error; compressive sensing (CS); maximum correntropy criterion (MCC); outlier; robust direction-of-arrival (DOA) estimation; OF-ARRIVAL ESTIMATION; LOCALIZATION; ESPRIT; GAIN;
D O I
10.1109/LSP.2017.2708659
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
In this letter, we propose a robust direction-of-arrival (DOA) estimation algorithm in the context of sparse reconstruction, where some array sensors are miscalibrated. In this case, conventional DOA estimation algorithms suffer from degraded performance or even failed operations. In the proposed approach, the miscalibrated sensor observations are treated as outliers, and a weighting factor is adaptively optimized and applied to each sensor in order to effectively mitigate the effect of the outliers. An algorithm based on the maximum correntropy criterion is then developed to yield robust DOA estimation. The simulation results are presented to verify the effectiveness and superiority of the proposed approach compared with conventional DOA estimation algorithms.
引用
收藏
页码:1073 / 1077
页数:5
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