Modelling, Detection, and Classification of Random Underwater Acoustic Transients

Common solutions for the problem of random transient classical optimum detector for random signals in noise. However, such a detector does not explicitly use the non-stationary character of the signal as a priori available information. Reformulation of the optimum detection in the time-frequency plane allows one to exploit this distinguishing signal feature and suppress noise. This is accomplished here by use of the Wigner-Ville signal representation and an optimum signal/noise subspace decomposition that improves the transient signal to noise ratio. The new detection/classification procedure eliminates the subspace where major part of the energy of random noise sample will fall.