Target detection from TVSS shallow-water data using a multichannel subband adaptive filtering scheme

In processing the Toroidal Volume Search Sonar (TVSS) data, the primary challenge is to detect targets in highly reverberant environments. This may be done by processing each sonar channel separately and estimating the time delays associated with the specular returns and then isolating these components from the background noise prior to beamforming. However, if there is significant reverberation it is difficult to accurately estimate time delays using only one sonar channel. Therefore, a multi-channel method is introduced that exploits the interdependency of adjacent sonar stave data. The method starts by enhancing signal to noise by combining multiple stave data after suitable phase compensation for array geometry. Next, time delays of the specular returns are estimated from the discrete wavelet sub-bands of the combined signal using a least squares method. The new method has been tested on several TVSS data sets, and the results are promising for even the most reverberant cases.