Joint estimation of frequency and DOA with spatio-temporal under sampling

In order to estimate the frequency and DOA of an incident signal with sub-Nyquist spatio-temporal sampling, A novel joint estimation algorithm based on spectrum correction and Chinese remainder theorem (CRT) was proposed. Firstly, the incident signal was parallelly sampled at multiple sensors non-uniformly located in a sparse linear array. Then, AM spectrum corrector was employed to extract the remainders of frequency and phase-difference from a small quantity of snapshots. Finally, implementing the close-form CRT on these remainders directly yields the estimates of frequency and DOA. In the proposed scheme, the spectrum corrector was shared by both the frequency estimator and the DOA estimator, which contributed to a high utilization of the snapshots. Furthermore, compared to the existing CRT based estimators, the proposed estimator needs not to incorporate multiple times of temporal undersampling on a single sensor, which saves considerable time consumption and thus obtain higher ability of tracking time-variant objects. Simulations verify the feasibility and the high-accuracy of the proposed joint estimator and further study shows that high reconstruction probability can be realized even in low SNR cases, which present the vast potential for future development. © 2016, Editorial Board of Journal on Communications. All right reserved.