We show that any weighted spatial smoothing (WSS) of subarray covariance matrices with nonzero weights will lead to a decorrelation of signals, and we discuss the consequences of using negative weights. We next propose a WSS that will eliminate correlated noise and establish a relationship between the WSS and covariance differencing. Finally, we present numerical results to demonstrate the effectiveness of the proposed WSS.
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Tan et al. (1997) studied this question.
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