MUSIC Algorithm for Direction of Arrival Estimation

This article presents the application of the MUSIC (Multiple Signal Classification) algorithm for Direction of Arrival (DOA) estimation. This high-resolution algorithm is particularly effective for estimating angles of arrival of multiple signals and has been widely adopted in various fields including radar systems, wireless communications, and array signal processing. The implementation typically involves constructing a covariance matrix from received signals, performing eigenvalue decomposition to separate signal and noise subspaces, and then searching for peaks in the MUSIC spatial spectrum. The accompanying compressed package contains carefully selected reference materials and well-structured code implementations. These resources demonstrate key algorithm components such as: array manifold vector calculation, covariance matrix estimation, eigenvalue decomposition using functions like numpy.linalg.eig (Python) or eig (MATLAB), and spectral peak search routines. The code includes comprehensive comments and follows best practices for numerical stability and computational efficiency. These high-quality resources provide substantial support for researchers and practitioners in both theoretical understanding and practical implementation. Users can adapt the provided codebase according to their specific requirements, gaining deeper insights into algorithm optimization and real-world application scenarios. We hope these supplementary materials offer valuable inspiration and assistance for your DOA estimation projects.