Augmented Tensor MUSIC for DOA Estimation Using Nested Acoustic Vector-Sensor Array

Nested acoustic vector sensor (AVS) arrays have attracted growing interest, and their performance can be further improved by assembling AVSs with spatially separated (SS) configurations. Following this trend, we propose an augmented tensor-MUSIC (AT-MUSIC) method for SS-AVSs while exploiting the inherent multidimensional structure of the array data. The implications of 'augmented' are twofold: (i) conventional tensor models based on co-centered AVSs are generalized to the case of SS-AVSs, and (ii) available information is fully utilized by judiciously arranging and aggregating the received data. Finally, we show the enhanced performance of AT-MUSIC in simulations.