Accelerated Adaptive Algorithms with Application to Direction-of-Arrival Estimation by Subspace Tracking

摘要

Direction-of-arrival (DOA) estimation based on subspace methods has collected much interest over a few decades, and adaptive DOA estimation with rapidly changing parameters will be necessary for wireless communications. This paper is concerned with a new subspace tracking scheme by using an accelerated LMS and RLS algorithms for time-varying parameters. The proposed accelerated adaptive algorithms are based on the internal model principle by approximately expressing the changing parameters by an expansion of polynomial time functions. Thus its application to DOA estimation based on the MUSIC and MODE schemes is presented and the effectiveness is validated in numerical simulations.