Underdetermined DOA estimation for moving array with reduced mutual coupling in unknown nonuniform noise environment

Abstract

In practice, direction of arrival (DOA) estimation methods will suffer from significant performance degradation due to limited physical sensors, mutual coupling effect and unknown nonuniform noise. To improve the performance of underdetermined DOA estimation in the case, this paper proposes a moving sparse uniform linear array (ULA) for more degrees of freedom (DOF) and lower mutual coupling, and then provides an estimation algorithm with unknown nonuniform noise mitigation. There is a systematic procedure to determine the inter-sensor spacing of the original array and number of shifted arrays for the synthetic ULA, for achieving increased DOF. The construction and analysis of mutual coupling matrix are exploited to show the reduced mutual coupling in the synthetic array. A procedure of nonuniform noise suppression for the synthetic array is given by averaging the noise power from the original array, and then root-MUSIC is employed for DOA estimation with low-complexity. Simulation results are given to demonstrate the superiority of the proposed array and algorithm in terms of DOF enhancement, mutual coupling reduction and nonuniform noise mitigation.