Mmse-Based Autocorrelation Sampling For Comprime Arrays

Sampling the physical-array autocorrelations is the initial processing step in standard direction-of-arrival (DoA) estimation with coprime arrays. These samples are then organized into an autocorrelation matrix estimate of a uniform-linear virtual coarray, which in turn is used for DoA estimation. Existing autocorrelation-sampling approaches provide the exact coarray autocorrelation matrix for asymptotically large sample support; however, they attain arbitrary/suboptimal mean-squared estimation error (MSE) for limited/low sample support. In this work, we present a minimum-MSE (MMSE) approach for autocorrelation sampling. The proposed method offers a superior autocorrelation-matrix estimate that can attain higher DoA estimation accuracy than the standard counterparts.