Efficient Direction-of-Arrival Estimation Method Based on Variable-Step-Size LMS Algorithm

Conventional direction-of-arrival (DOA) estimation methods based on subspace decomposition are computationally complex and difficult to implement in practical applications. Although a fixed-step-size least mean square (FSS-LMS) algorithm for DOA estimation has overcome the complexity problem; however, the manual selection of suitable step size is difficult. In this letter, a variable-step-size LMS algorithm is proposed for DOA estimation. In the proposed method, the step size is updated by using the estimated signal power and the cumulative sum of squared instantaneous error, and the spatial spectrum is obtained by the reciprocal of array pattern, where the peak values indicate the estimated DOAs of signals. The proposed method can choose step size adaptively and provide better performance with low computational complexity. The performance of proposed method is verified by the numerical simulations and compared with some existing methods.