Joint DOA and frequency estimation with sub-Nyquist sampling based on trilinear decomposition and SVD
Liang Liu, Ping Wei, Huaguo Zhang · 2017
In the previous work for joint Direction-Of-Arrival (DOA) and frequency estimation with sub-Nyquist sampling, algorithm JDFTD has a superior estimation performance. However, the computational burden increases with the snapshot for iterative operation. In this paper, singular value decomposition (SVD) is employed to eliminate the effect of snapshot and a new version of algorithm JDFTD based on SVD (SVD-JDFTD) is proposed. Numerical simulations verify that SVD-JDFTD reduces the computational burden without loss the superior estimation performance of JDFTD.