A New Sparse Bayesian Learning-Based Direction of Arrival Estimation Method with Array Position Errors

Yu Tian, Xuhu Wang (), Lei Ding, Xinjie Wang, Qiuxia Feng and Qunfei Zhang
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Yu Tian: School of Information and Control Engineering, Qingdao University of Technology, Qingdao 266520, China
Xuhu Wang: School of Information and Control Engineering, Qingdao University of Technology, Qingdao 266520, China
Lei Ding: School of Information and Control Engineering, Qingdao University of Technology, Qingdao 266520, China
Xinjie Wang: School of Information and Control Engineering, Qingdao University of Technology, Qingdao 266520, China
Qiuxia Feng: School of Information and Control Engineering, Qingdao University of Technology, Qingdao 266520, China
Qunfei Zhang: School of Marine Science and Technology, Northwest Polytechnical University, Xi’an 710129, China

Mathematics, 2024, vol. 12, issue 4, 1-17

Abstract: In practical applications, the hydrophone array has element position errors, which seriously degrade the performance of the direction of arrival estimation. We propose a direction of arrival (DOA) estimation method based on sparse Bayesian learning using existing array position errors to solve this problem. The array position error and angle grid error parameters are introduced, and the prior distribution of these two errors is determined. The joint probability density distribution function is established by means of a sparse Bayesian learning model. At the same time, the unknown parameters are optimized and iterated using the expectation maximum algorithm and the corresponding parameters are solved to obtain the spatial spectrum. The results of the simulation and the lake experiments show that the proposed method effectively overcomes the problem of array element position errors and has strong robustness. It shows a good performance in terms of its estimation accuracy, meaning that the resolution ability can be greatly improved in the case of a low signal-to-noise ratio or small number of snapshots.

Keywords: direction of arrival estimation; array position error; sparse Bayesian learning; expectation maximization (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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