Subspace intersection method of high-resolution bearing estimation in shallow ocean using acoustic vector sensors

Subspace intersection using acoustic vector sensors by extracting main eigenspace of modal subspace

“…We consider the Pekeris Ocean model as [5]. The ocean model is shown in Figure1.The channel parameters are assumed to be the following: water depth H=75m,sound speed in water c=1500m/s, sound speed in bottom c b =1700m/s, density of water , density of bottom , attenuation in bottom where , and .…”

“…All the results have been obtained by averaging over 200 simulations, and the snapshots isL=350. The signal-to-noise ratio for the source is defined as [5]. …”

“…Some methods were presented to solve this problem such as least square subspace intersection [3] and compressing the modal space subspace intersection [4]. Nagananda [5] extend SI to an AVS array which measure acoustic pressure as well as all components of particle velocity, and AVS array get better performance than scalar array, but stability is not improved.…”

“…Since correlation matrix of noiseis not diagonal, so it needs to be whitened before signal processing. In order to satisfy this condition, we apply the whitening transformation * = w n W n , where the matrix W is given in [5]. So we get…”

“…The subspace intersection method using acoustic vector sensors [5] provides unbiased bearing estimates in a range-independent shallow ocean with the advantage of both subspace intersection(SI) method and acoustic vector sensors(AVS) array. But its robustness is poor.…”