Particle-Velocity Coarray Augmentation For Direction Finding with Acoustic Vector Sensors
In this paper, the problem of passive direction finding is addressed using an acoustic vector sensor array (AVS), which may be deployed either in free space or near a reflecting boundary. Building upon the $4 \times 1$ vector field measured by an AVS, the particle-velocity coarray augmentation (PVCA) is proposed to admit the underdetermined direction finding using the spatial difference coarray derived from the vectorization of the array covariance matrix. Unlike the widely used spatial coarray Toeplitz recovery technique, the PVCA is applicable to arbitrary array geometries and imposes no reduction of the spatial difference coarray aperture. For the array located at or near a reflecting boundary, the PVCA allows resolving up to $13$ sources, while for the array located in free space, the PVCA can identify $9$ sources at most. By applying to the systematically designed nonuniform arrays, such as coprime arrays and nested arrays, the PVCA can be coupled with the spatial smoothing technique to get the number of resolvable sources multiplied. Finally, the efficacy of the PVCA is verified by numerical simulations.