MUSIC Algorithm - Multiple Signal Classification for Spatial Spectrum Estimation

MUSIC (Multiple Signal Classification) is a method used for spatial spectrum estimation and DOA (Direction of Arrival) estimation. The power spectrum estimation is based on matrix eigenvalue decomposition. This approach includes two non-parametric estimation methods: eigenvector estimation and MUSIC estimation. Eigenvector estimation is mainly suitable for power spectrum estimation of sinusoidal signals mixed with white noise, while the MUSIC estimation method is more appropriate for general sinusoidal signal parameter estimation. MUSIC, an abbreviation for Multiple Signal Classification, represents a powerful signal processing technique. In implementation, the algorithm typically involves computing the signal covariance matrix, performing eigenvalue decomposition to separate signal and noise subspaces, and then constructing the MUSIC pseudospectrum using the orthogonality between signal directions and noise eigenvectors. The peak detection in the pseudospectrum yields the DOA estimates with superior resolution compared to conventional methods.