Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/170201
Title: Robust DOA Estimation in the Presence of Miscalibrated Sensors
Authors: Ben Wang;Yimin D. Zhang;Wei Wang
Year: 2017
Publisher: IEEE
Abstract: 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.
URI: http://localhost/handle/Hannan/170201
volume: 24
issue: 7
More Information: 1073,
1077
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7934414.pdf311.3 kBAdobe PDF
Title: Robust DOA Estimation in the Presence of Miscalibrated Sensors
Authors: Ben Wang;Yimin D. Zhang;Wei Wang
Year: 2017
Publisher: IEEE
Abstract: 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.
URI: http://localhost/handle/Hannan/170201
volume: 24
issue: 7
More Information: 1073,
1077
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7934414.pdf311.3 kBAdobe PDF
Title: Robust DOA Estimation in the Presence of Miscalibrated Sensors
Authors: Ben Wang;Yimin D. Zhang;Wei Wang
Year: 2017
Publisher: IEEE
Abstract: 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.
URI: http://localhost/handle/Hannan/170201
volume: 24
issue: 7
More Information: 1073,
1077
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7934414.pdf311.3 kBAdobe PDF