Localization of underwater moving sound source based on time delay estimation using hydrophone array

8th International Conference on Physics and its Applications

Rahman, S.A.^1 ; Arifianto, D.^1 ; Dhanardono, T.^1 ; Wirawan^2

Engineering Physics Department, Faculty of Industrial Technology, Institut Teknologi Sepuluh Nopember, Indonesia^1

Electrical Engineering Department, Faculty of Industrial Technology, Institut Teknologi Sepuluh Nopember, Jl. Arief Rahman Hakim, Surabaya

0111, Indonesia^2

关键词: Characteristics of sounds;    Cross correlations;    Generalized cross correlations;    Moving sound source;    Real environments;    Stationary positions;    Time delay estimation;    Uniform linear arrays;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/776/1/012075/pdf
DOI  :  10.1088/1742-6596/776/1/012075

来源: IOP

【 摘 要 】

Signal and noise of an underwater moving sound source is used to track the azimuth of a target. Uniform linear array with four hydrophones is used to detect azimuth of target by obtain the time delay information to get azimuth information. Success rate of time delay estimation influenced by characteristics of sound propagation like reflection, reverberation, etc. Experiment in real environment was done to analyze performance of the cross correlation (CC) and generalized cross correlation with the phase transform (PHAT) weighting to estimate time delay between two signal. The simulation done by convolute two signal that has been given time delay and impulse response of the medium test. Then the time delay of two signal estimated by CC and PHAT algorithm in Matlab in the various SNR. Then the algorithm tested in a pool to detect stationary and moving position of sound source. Result of the simulation and experiment in real environment shown that PHAT better than CC. The best azimuth tracking achieved by using PHAT algorithm with error of 0 - 9.48 degree in stationary position. In moving sound experiments, tracking the bearing and azimuth of the mini vessel (sound source) can be done by time delay estimation using PHAT.