Augmented subspace MUSIC method for DOA estimation using acoustic vector sensor array

In the scenario of ambient noise, the noise powers received by the pressure and velocity components in an underwater acoustic vector sensor (AVS) array are unequal. This paper proves when using the MUSIC method, this inequality causes virtual sources and thus increases the rank of the signal subspace. This fact dramatically degrades the DOA estimation performance of the MUSIC method. Then, an augmented subspace (AS) MUSIC method is proposed to take account of the virtual sources, by augmenting the number of the virtual sources into the signal subspace. Simulation results demonstrate in the case of a high signal-to-noise ratio (SNR), the performance of the AS MUSIC method and the MUSIC method is similar. However, in the case of a low SNR, the AS MUSIC method is superior to the MUSIC method in terms of spatial spectrum, estimation accuracy, and resolution. Experimental results further verify the superiority of the AS MUSIC method over the MUSIC method.