Using least squares to improve blind signal copy performance

Conventional methods for signal copy require one to estimate the directions of arrival (DOA´s) of the signals prior to computing the weight vectors. Blind copy algorithms alleviate the need for DOA estimation (and hence the need for array calibration data) by exploiting the temporal rather than spatial structure of the signals, but they converge slowly in some cases. In this letter, we present a simple technique that uses both spatial and temporal information to improve signal copy performance. Specifically, the algorithm uses an initial blind estimate of the signals to compute a least-squares estimate of the array response, which in turn is used to update the signal estimates.<>