The invention belongs to the field of array
signal processing, and in particular relates to a fast
target angle estimation method based on sparse Bayesian learning. The method comprises the followingsteps of S1, performing initialization on the parameters to be estimated of gammaj and sigma0, wherein j is equal to 1,2 to N; S2, quickly obtaining
signal posterior probability density functions at each moment by using the AMP
algorithm; S3, updating values of the parameters to be estimated of gammaj and sigma0 by using the EM
algorithm, wherein j is equal to 1,2 to N; and S4, determining whetherthe update iterative process of the parameters to be estimated converges, returning to the S2 to re-iterate if not, and if so,
jumping out of the loop and determining the direction and quantity of the target incoming
waves. The method provided by the invention can improve the low
signal-to-
noise ratio and the multi-objective angle
estimation accuracy under
small sample conditions, and has the advantages of fast iterative convergence speed and high computational efficiency for estimating the
target angle, which can be applied to the real-time multi-objective angle
estimation system and has important
engineering application value.