A Fast and Robust MUSIC Algorithm for Estimating Multiple Coherent Signals

The conventional MUSIC algorithm demonstrates subpar performance in estimating coherent signals from multiple targets and yields unreliable results. Moreover, it suffers from high computational complexity and sluggish processing speed when applied to extensive datasets involving multiple sensors. In order to tackle these challenges, this paper presents an enhanced and expedient version of the MUSIC algorithm for estimating multiple coherent signals. Drawing upon the ROOT-MUSIC algorithm, which is based on the propagation operator, this algorithm introduces a spatial smoothing technique by substituting the original covariance matrix with the average of subarray covariance matrices. Simulation results demonstrate that the proposed algorithm not only resolves the issue of estimating multiple coherent signals but also achieves exceptional performance in terms of robustness and computational speed, even under low signal-to-noise ratio conditions.