Improved signal copy with partially known or unknown array response

Blind adaptive algorithms extract signals that overlap in time and frequency by exploiting their temporal structure, but ignore any available spatial (array response) data. On the other hand, direction-finding based methods compute the signal copy weights using estimates of the signal directions, but ignore information about signal structure. In this paper, we present two simple iterative techniques that attempt to incorporate both temporal and spatial information in estimating the signal waveforms received by an array of sensors. The first technique assumes an initial blind signal estimate is available, and uses least-squares to approximate the array response and refine the signal estimate. The second method is applicable to digitally modulated signals, and uses bit decisions made on an initial signal estimate to recompute the signal copy weight vectors. A theoretical performance analysis of both algorithms is conducted for the high SNR case, and some representative simulation results are included