Signal Selection for Robust Matched Filtering

The optimum signal selection problem under a power constraint for minimax robust discrete-time finite-length matched filtering is studied. The classical solution, which is to choose the signal as a minimum-eigenvalue eigenvector of the noise covariance matrix, is generalized to cases in which the transmitted signal is subject to channel distortion modeled by mean-square, maximum-absolute, and mean-absolute distortion uncertainty classes.