Decorrelation performance of DEESE and spatial smoothing techniques for direction-of-arrival problems

Second-order spatial analysis methods for array signal processing have been shown to yield high resolution by exploiting specific eigenstructure properties of the array output covariance matrix. However, when some of the signals are coherent, these covariance-based methods face serious difficulties produced by smaller rank. In this correspondence, a theoretical expression is derived for the effective correlation coefficient between sources after processing when using spatial smoothing and a new scheme of space diversity called DEESE (decomposition de l´espace source estime). Monte-Carlo simulations have been used to compare DEESE and spatial smoothing and to show the advantages of using DEESE when noise is present