Abstract
The principle of acoustic energy flux detection method using a single micro electromechanical system (MEMS) vector hydrophone is analyzed in this paper. The probability distribution of acoustic energy flux and the weighted histogram algorithm are discussed. Then, an improved algorithm is proposed. Based on the algorithm, the distribution range of the energy is obtained by a sliding window, the energy center of gravity in the range is considered as the result of direction of arrival (DOA) estimation, and it is proved to be the maximum likelihood estimation of the target direction. The simulation results show that, with the signal to noise ratio (SNR) from −10 dB to 10 dB, the root mean square error (RMSE) of the improved algorithm is reduced by 47.8% on average, and is more accurate in the presence of interference. The experimental results of lake test are consistent with the theory analysis and simulation results.
Highlights
When the bandwidth of the sound source is known, a single micro electromechanical system (MEMS) vector hydrophone can be used to estimate the direction of target by acoustic energy flux detection by Equation (11)
After the target acoustic energy flux distribution range is obtained, the target direction is calculated by the energy center of gravity method in this range, and this direction is the result of direction of arrival (DOA) estimation
Conclusions estimation using a single MEMS vector hydrophone are studied in this paper
Summary
The hydrophone array is generally adopted in underwater detection for direction of arrival (DOA) estimation, which requires great physical space [1]. A single MEMS vector hydrophone is capable of DOA estimation [4], suitable for limited deployment space of equipment. The study on DOA estimation algorithm using a single MEMS vector hydrophone is of strongly practical significance. The average sound intensity algorithm is a common method for DOA estimation for vector hydrophone. It can suppress isotropic incoherent interference and has a small computation burden, but cannot distinguish more than one target [5]. There are other algorithms based on power spectrum estimation or subspace analysis, including beam-forming [9], multiple signal classification (MUSIC) [10]. Weighted histogram algorithm principle is discussed, single MEMS vector hydrophone. Gaussto satisfy thecondition far-field condition and in thethe noise in the environment is white isotropic white ian noise. noise
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