Abstract: Matched field processing technology (MFP) is a general passive localization method for underwater sound source due to its advantages in ultra-long distance positioning. In this paper, assume the total number of hydrophones remains unchanged, a single hydrophone array is divided into multiple hydrophone sub-arrays for independent positioning, and the positioning results of sub-arrays are fused to reduce the impact of noise and improve the robustness of the positioning system. Based on the traditional Bartlett processor, we derive the formula for average positioning error which varies with signal to noise ratio (SNR) and the number of hydrophones. The formula is used to decide the optimal structure of sub-arrays, i.e., the number of sub-arrays and the number of hydrophones in each sub-array. Experiments and simulations proves that multiple sub-arrays can improve the positioning accuracy compared with the single hydrophone array in the noisy environment. The average positioning errors produced by the experiments are consistent with the numerical ones based on the theoretical analysis.

Shuo Jin and Xiukui Li, “Multiple Hydrophone Arrays based Underwater Localization with Matching Field Processing” International Journal of Advanced Computer Science and Applications(IJACSA), 13(3), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0130375

@article{Jin2022,
title = {Multiple Hydrophone Arrays based Underwater Localization with Matching Field Processing},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0130375},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0130375},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {3},
author = {Shuo Jin and Xiukui Li}
}