Modified MUSIC Algorithm for DOA Estimation of Coherent Signal Sources

This article mentions the MUSIC algorithm for Direction of Arrival (DOA) estimation of coherent signal sources but lacks detailed explanation of its specific content and implementation process. Below are some possible supplements and explanations. The MUSIC (Multiple Signal Classification) algorithm is a high-resolution spectral estimation method used for estimating directions of multiple signal sources. The core concept involves separating the signal subspace from the noise subspace to derive signal DOAs. Implementation typically requires steps such as signal acquisition, spatial spectrum estimation, and decomposition of signal/noise subspaces. In code implementation, key functions would include covariance matrix computation (using functions like cov() or eigenvalue decomposition), subspace separation via Singular Value Decomposition (SVD), and peak detection in spatial spectrum plots. Compared to other DOA estimation algorithms, MUSIC offers advantages like high accuracy and resolution, making it widely adopted in signal processing applications such as radar and wireless communications. For coherent sources, modifications like spatial smoothing or forward/backward averaging are often implemented to decorrelate signals before applying standard MUSIC procedures.