Subspace-based single-vector-sensor direction finding for two coherent acoustic sources having real-valued constellations

Perfect correlations between the three particle velocity components and acoustic pressure of an acoustic source effect an efficient aperture for a solitary acoustic vector-sensor which is able to simultaneously collect the acoustic pressure and three orthogonal particle velocity components. Single-vector sensor direction finding for non-coherent signals is thus possible. For coherent signals, source decorrelation is required by many computationally attractive direction finding algorithms such as spatial filtering methods and subspace-based methods to recover the rank property of the source covariance matrix. Conventional source decorrelation techniques such as spatial smoothing and angular smoothing necessitate averaging of several shifted in-variance subarrays, which is impossible for one acoustic vector-sensor. To solve the problem of rank deficiency, a novel method called phasic smoothing is herein suggested and validated for source decorrelation and direction finding of two coherent noncircular signals with one acoustic vector-sensor.