Underwater target detection using multichannel subband adaptive filtering and high-order correlation schemes

In this paper, new pre- and post-processing schemes are developed to proces s shallow-water sonar data to improve the accuracy of target detection. A m ultichannel subband adaptive filtering is applied to preprocess the data in order to isolate the potential target returns from the acoustic backscatte red signals and improve the signal-to-reverberation ratio. This is done by estimating the time delays associated with the reflections in different sub bands, The preprocessed results are then beamformed to generate an image fo r each ping of the sonar. The testing results on both the simulated and rea l data revealed the efficiency of this scheme in time-delay estimation and its capability in removing most of the competing reverberations and noise, To improve detection rate while significantly minimizing the incident of fa lse detections, a high-order correlation (HOC) method for postprocessing th e beamformed images is then developed. This method determines the consisten cy in occurrence of the target returns in several consecutive pings, The ap plication of the HOC process to the real beamformed sonar data showed the a bility of this method for removing the clutter and at the same time boostin g the target returns in several consecutive pings, The algorithm is simple, fast, and easy to implement.