Investigate and measure the angular accuracy of ML, MUSIC, Root-MUSIC algorithms and spatial smoothing in signal detection

In this paper, we first simulate ML, MUSIC, Root-MUSIC algorithms and space smoothing in noisy and fiddling environments, and then these algorithms are compared in terms of estimating the accuracy of the angles received from the two sources. By presenting the simulation results of four algorithms in the form of tables that are based on mean, deviation from mean, variance of estimated angles and the percentage of successful experiments, it is observed that Root-MUSIC and MUSIC algorithms in terms of estimation and Detecting close angles is more accurate. In these two methods, the angles close to each other, up to about one degree, can be detected and separated. In addition, simulation results show that spatial smoothing algorithm is the most effective way to identify coherent resources.