A CCM-Based Joint DOA-Frequency Estimation and Signal Recovery with Efficient Sub-Nyquist Sampling
Liang Liu, Zhouchen Li, Jiancheng An, Lu Gan, Hongbin Li
Abstract
This paper addresses key challenges caused by high sampling rates in wideband joint spectrum sensing applications. A joint Direction of Arrival (DOA) and frequency estimation algorithm is proposed by utilizing the Cross-Covariance Matrix (CCM) constructed from the outputs of an efficient undersampling array receiver with multiple elements, only one of which is connected with multiple time-delay branches. In contrast to previous autocorrelation-based methods, the proposed method reduces the impact of noise and doubles the maximum unit time-delay, resulting in improved estimation performance. Additionally, it does not impose restrictions on the number of array sensors and time-delay channels, which allows for more flexibility in the allocation of resources for the receiver. In the simulation, the proposed algorithm demonstrates outstanding performance.
BibTeX
@inproceedings{icassp2024_accmbasedjointdo,
title = {A CCM-Based Joint DOA-Frequency Estimation and Signal Recovery with Efficient Sub-Nyquist Sampling},
author = {Liang Liu and Zhouchen Li and Jiancheng An and Lu Gan and Hongbin Li},
booktitle = {ICASSP 2024},
year = {2024}
}