Linear Chirp Signal DOA Estimation Using Sparse Time–Frequency Dictionary

This paper is concerned with the estimation of the directions-of-arrival (DOA) of multiple linear chirp signals. We construct a novel time-frequency dictionary based on the properties of chirp signals in the fractional Fourier domain, and a sparse reconstruction algorithm is proposed to achieve high performance. Then, the errors resulting from the off-grid model mismatch is considered, and the dictionary matrix is reformulated into a multiplication of a fixed matrix and a sparse matrix. Further, an iterative alternating approach is proposed to improve the accuracy of the DOA estimates. The proposed algorithm provides better estimation, anti-correlation performances and increased resolution than Multiple Signal Classification (MUSIC) and the time–frequency MUSIC (TF-MUSIC) based on the spatial time–frequency distributions. Simulation results demonstrate the effectiveness of the proposed approach.