Utilization of Noise-Only Samples in Array Processing With Prior Knowledge

Abstract

For array processing, we consider the problem of estimating signals of interest, and their directions of arrival (DOA), in unknown colored noise fields. We develop an estimator that efficiently utilizes a set of noise-only samples and, further, can incorporate prior knowledge of the DOAs with varying degrees of certainty. The estimator is compared with state of the art estimators that utilize noise-only samples, and the Cramér-Rao bound, exhibiting improved performance for smaller sample sets and in poor signal conditions.