Hypercomplex Model of Acoustic Vector Sensor Array with Its Application for the High Resolution Two Dimensional Direction of Arrival Estimation

In this paper, a hypercomplex model of acoustic vector sensor arrays is first introduced. Namely, the hypercomplex number is used to model the four components of the output signals of an acoustic vector sensor in a holistic manner. Then we use the MUSIC-like algorithm based on the hypercomplex eigenvalue decomposition to estimate the direction of arrival (DOA) of the signals. Both theoretical and simulation results show that that the presented method with the same estimation accuracy as the long vector ones can reduce 75% memory requirements and half division operations.