Applications of wavelet subband decomposition in adaptive arrays

Pre-processing radar signals incident on an adaptive array by applying an invertible transformation such as wavelets is the focus of this study. The effect of wavelet subband decomposition of radar signals prior to adaptation using an LMS algorithm or an Applebaum processor on the adaptation rate of these processors is examined. Faster adaptation rates can be achieved by inserting a wavelet transformer between the incoming signal and the LMS or Applebaum array processors. The transformation improves the condition number of the covariance matrix and thus improves the convergence rate of an array.<>