MUSIC Enhancement Algorithm for Subspace-based DOA Estimation in Smart Antenna Systems

In smart antenna systems, subspace-based algorithms for Direction of Arrival (DOA) estimation play a critical role. Among these, the MUSIC (Multiple Signal Classification) algorithm stands as one of the most widely used techniques, capable of effectively handling multipath signals and accurately estimating signal source directions even when the number of signal sources is uncertain. The algorithm implementation typically involves calculating the signal covariance matrix, performing eigenvalue decomposition to separate signal and noise subspaces, and constructing the MUSIC spectrum for peak detection. However, to further enhance MUSIC algorithm performance, various improvements have been developed. One significant enhancement involves incorporating prior information during signal source number estimation to achieve more accurate direction finding. This improved approach has been validated in technical literature and has been extensively applied in practical smart antenna system implementations. The modification typically requires adjusting the source number estimation subroutine and optimizing the eigenvalue threshold determination process in the code implementation.