A DOA Estimation Algorithm with No Angle Ambiguity for SULA of FMCW Radar

Direction-of-arrival (DOA) estimation plays a crucial role in signal processing of frequency-modulated continuous wave (FMCW) radar. However, traditional DOA estimation algorithms, such as multiple signal classification (MUSIC), encounter new challenges when applied to sparse arrays with a large aperture and high resolution. Particularly, angle ambiguity is inevitable when utilizing sparse uniform linear array (SULA) which features a larger aperture and fewer mutual-coupling effects. In this paper, a new DOA estimation model is derived based on FMCW echo signal, and the DOA estimation problem is converted into a semidefinite program (SDP) problem based on ANM method, avoiding grating lobes or phase ambiguity caused by sparse arrays. Moreover, an alternating direction method of multipliers (ADMM) approach was introduced to accelerate the convergence rate and achieve unambiguous DOA estimation. Simulation experiments validated the effectiveness of the proposed algorithm.