The algorithms of estimating bispectrum and cross-bispectrum based on acoustic vector signal
Sichu Li · Shengxue jishu · 2008
The algorithms of estimating bispectrum and cross-bispectrum based on acoustic vector signal are proposed and the detail steps are given. The proposed algorithms are applied to feature extraction from two types of underwater acoustic targets. And the features construct input vector set of LMBPNN. The identification of underwater acoustic targets can then be made based on the extracted features. The identification results show the effectiveness of the proposed algorithms. And it has been seen by experiments that the recognition rate for Class B targets is superior to that for Class A targets. This is because the characteristic frequencies of Class B targets are relatively more concentrated than that of Class A targets. Furthermore, the fact that the classification performance of using the cross-bispectrum is superior to that of using the bispectrum is in coincidence with the fact that the performance of the joint processing of pressure and particle velocity is superior to that of the single processing of pressure or particle velocity.