Multiple Signal Classification Method

This method employs the classic MUSIC (MUltiple SIgnal Classification) algorithm, designed for angular separation of multiple mixed signals. The algorithm finds extensive applications in signal processing domains including antenna array processing in wireless communication systems, medical imaging, seismic exploration, and radar imaging. The implementation involves processing signals received by multiple sensors through covariance matrix computation and eigenvalue decomposition to estimate direction of arrival (DOA). Key steps include: 1) Computing the signal covariance matrix from sensor array data 2) Performing eigenvalue decomposition to separate signal and noise subspaces 3) Constructing the MUSIC spectrum using noise subspace eigenvectors 4) Identifying spectral peaks to determine signal source angles. This subspace-based approach significantly enhances signal processing accuracy by effectively separating mixed signals and resolving closely spaced sources beyond the Rayleigh resolution limit.