Enhanced DOA Estimation Exploiting Multi-Frequency Sparse Array

In this paper, we develop a general framework of multi-frequency sparse array to estimate the direction-of-arrival (DOA) of a significantly higher number of targets than the number of physical sensors. The multi-frequency sparse arrays are designed to offer zero lag redundancy in the rendered difference coarray so that the available degrees of freedom are fully utilized to enable high-resolution DOA estimation. A modified sensor interpolation technique is developed to accurately estimate the signal correlation matrix so that the effect of holes in the difference coarray is mitigated. The proposed technique accounts for both self-lags between signals corresponding to the same frequencies and the cross-lags between signals corresponding to different frequencies. As such, it enhances the DOA estimation performance compared to existing methods that either perform array interpolation utilizing only the self-lags or carry out group sparse reconstruction without exploiting array interpolation. Simulation results verify the offerings of the multi-frequency sparse arrays.

Automated summary

This paper presents a general framework of multi-frequency sparse array for estimating the direction-of-arrival of a significantly higher number of targets than the number of physical sensors. By providing zero lag redundancy and developing a modified sensor interpolation technique, the framework enables high-resolution DOA estimation and mitigates the effect of holes in the difference coarray. The proposed technique enhances the DOA estimation performance by considering both self-lags and cross-lags between signals corresponding to different frequencies, compared to existing methods. Simulation results verify the effectiveness of the multi-frequency sparse arrays.