DOA Estimation of Coherent Signal Using MUSIC Algorithm with Nonuniform Sampling

The channel outputs are sampled on nonuniform sampling sets, and an analysis of the decorrelation based on nonuniform sampling (NUS) is investigated. It is demonstrated that MUSIC algorithm with NUS of various array elements may be capable of selecting the signal of interesting including the coherent group. NUS in the time domain is equivalent to alter the relative distance between sensors and leads to the radiant sources impinging the different arrays between two snapshots just as a virtual array spatial smoothing preprocessing. Simulations are conducted to verify that MUSIC based on nonuniformity of sensor sampling is effective to estimate direction-of-arrival (DOA) of incident signals in the coherent environment. Simultaneously, it's beneficial to greatly improve the estimation accuracy and angular resolution as a result of larger array aperture introduced but no angle-measure ambiguity and offer a better performance in lower SNR than weighted spatial smoothing (WSS) with MUSIC algorithm.