Off-Grid DOA Estimation Based on Alternating Iterative Weighted Least Squares for Acoustic Vector Hydrophone Array

Wei-dong, Wang; Zhang, Qunfei; Shi, Wentao; Tan, Weijie; Mao, Limi

doi:10.1007/s00034-020-01391-0

Cited by 6 publications

(1 citation statement)

References 41 publications

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“…Compared with scalar hydrophone, vector hydrophone can obtain more sound field information, not only the scalar information of the sound field, but also the vector information of the vibration velocity. The application of vector hydrophone array has been studied in the articles [37][38][39][40][41][42][43][44], but there are little articles focused on the vector hydrophone array design. For the vector hydrophone array, the above-mentioned array design methods still have the following problem which needs to be solved urgently: Previous works involving CS and sparse array design tended to focus on the case of scalar hydrophone arrays; that is, the above optimization method regards each channel of the vector hydrophone array element as one optimized position.…”

Section: Introductionmentioning

confidence: 99%

Vector Hydrophone Array Design Based on Off-Grid Compressed Sensing

Shi

Liang

Qiu

et al. 2020

Sensors

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Array design is the primary consideration for array signal processing, and sparse array design is an important and challenging task. In underwater acoustic environments, the vector hydrophone array contains more information than the scalar hydrophone array, but there are few articles focused on the design of the vector hydrophone array. The difference between the vector hydrophone array and the scalar hydrophone array is that each vector hydrophone has three or four channels. When designing a sparse vector hydrophone array, these channels need to be optimized at the same time to ensure the sparsity of the array elements’ number. To solve this problem, this paper introduced the compressed sensing (CS) theory into the vector hydrophone array design, constructed the vector hydrophone array design problem into a globally solvable optimization problem, proposed a CS-based algorithm with the L1 norm suitable for vector hydrophone array, and realized the simultaneous optimization of multiple channels from the same vector hydrophone. At the same time, the off-grid algorithm was added to obtain higher design accuracy. Two design examples verify the effectiveness of the proposed method. The theoretical analysis and simulation results show that compared with the conventional compressed sensing algorithm with the same aperture, the algorithm proposed in this paper used fewer vector hydrophone elements to obtain better fitting of the desired beam pattern.

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