Direction-of-arrival estimation algorithm of pyramid-shaped acoustic vector sensor array based on higher-order cumulants

In order to solve the direction-finding resolution problem of multi-sources in the low Signal-to-Noise Ratio (SNR) a virtual ESPRIT algorithm for a pyramid-shaped acoustic vector sensor array is proposed. Based on the array expansion and the Gaussian noise suppression of the fourth-order cumulants, the proposed algorithm calculates the fourth-order cumulants of different output components of the acoustic vector sensor, which is equivalent to put a virtual array with the same structure as the original array in the three-dimensional direction. By doing so, one can construct a rotation invariant matrix that includes angular information for direction-finding. By studying the Cramer-Rao Bound of the proposed algorithm, we show its performance is affected by the Signal-to-Noise Ratio (SNR), the number of snapshots and the elevation of the source. The simulation results show that the proposed algorithm has better noise suppression capability and higher resolution Direction-Of-Arrival (DOA) estimation performance than the traditional ESPRIT algorithm with acoustic vector sensor array.