An Improved Bearing Estimation Algorithm Using Acoustic Vector Sensor Array Based on Rotational Invariance Technique

To improve the performance of general bearing estimation algorithm using acoustic vector sensor array (AVSA) with rotational invariance technique (ESPRIT), an improved algorithm is proposed and carried out in this paper, which is based on the combination processing of pressure and particle velocity. The cross-covariance matrix of pressure and particle velocity was constructed by taking the mean value of cross-covariance matrixes under even-spacing driving angles and using ESPRIT. Simulation and test result on the lake environment show that the proposed algorithm is more effective than existing algorithms in resolution and accuracy under the case of low signal-to-noise ratio. The foundation of improved algorithm is the principle of coherency between pressure and particle velocity, which could suppress interference strongly in isotropic noise field. Moreover, with the use of ESPRIT algorithm, the AVSA could obtain much more gain and have advanced performance in azimuth angle estimation.