Introduction - If you have any usage issues, please Google them yourself
MUSIC algorithm is a matrix decomposition method based on feature space. From the geometric point of view, the observed spatial signal processing can be decomposed into signal subspace and noise subspace, it is clear that the two spaces are orthogonal. The signal received by the array to the subspace of the covariance matrix of the signal component corresponding eigenvectors, the noise subspace of the covariance matrix of all by the smallest eigenvalue (noise variance) eigenvectors corresponding to the composition. MUSIC algorithm is the use of orthogonal properties between these two complementary space to estimate the spatial orientation of the signal. Noise subspace of all vectors are used to construct the spectrum, all the spatial orientation of the spectrum corresponding to the peak position of the signal wave direction. MUSIC algorithm greatly improves the resolution measurements, while the antenna array adapted to any shape, but the prototype MUSIC algorithm requires to wave sign