Performance Analysis of the MUSIC Algorithm in the Presence of Correlated Noise

Passive direction finding has been studied over the past decades and theoretic performance prediction is a fundamental problem. The performance of the MUSIC algorithm for Direction-of-arrival (DOA) estimation under measurement uncertainty is analyzed. In the conventional MUSIC algorithm performance analysis, noise is assumed to be uncorrelated. In this paper, the noise correlation between antenna elements is considered according to the distance between antenna elements. The Mean Squared Error (MSE) obtained through Monte-Carlo simulations is compared with the MSE derived from analytical expressions. The primary contribution of this paper is to reduce the computational complexity of the performance analysis of the MUSIC algorithm compared to the existing Monte-Carlo simulation-based performance analysis. To our knowledge, no previous studies have derived a closed-form analytical performance analysis of the algorithm in the presence of correlated noise.