An eigenvalue/Eigenvector interpretation of surface reverberation rejection performance

The application of adaptive least-mean square (LMS) and least-squares lattice (LSL) algorithms to the rejection of sea surface reverberation is discussed. A specific dual channel noise cancelling structure is considered along with the results of processing a ping selected from an experimental ocean reverberation data set. A time-evolving eigenvalue/eigenvector decomposition is used to provide insight into the performance differences between the two adaptive algorithms in this highly dynamic physical geometry.