DOA Estimation Using the Classic MUSIC Algorithm

In the classic MUSIC (Multiple Signal Classification) algorithm, DOA (Direction of Arrival) estimation represents a crucial signal processing technique. DOA estimation determines the direction of signal sources by analyzing phase differences in received signals, typically implemented through covariance matrix decomposition and eigenvalue analysis. This technique finds extensive applications in audio signal processing, speech recognition, and wireless communication systems. In audio processing, DOA estimation enables optimal microphone array placement for superior recording quality by computing spatial spectra using steering vectors. For speech recognition applications, the algorithm facilitates source separation through subspace decomposition, significantly improving multi-speaker identification accuracy by resolving coherent signals. The implementation typically involves constructing a signal covariance matrix, performing eigenvalue decomposition to identify noise subspaces, and peak detection in the MUSIC spectrum for angle estimation. Given its robust performance in resolving multiple sources, DOA estimation technology demonstrates broad application prospects across various fields.