This invention addresses the high computational complexity of two-dimensional direct extensions of one-dimensional grid-based sparse target
azimuth estimation methods. It proposes a uniform
rectangular array target
azimuth estimation method based on array manifold matrix learning. The method includes: obtaining the expression for the array manifold matrix based on the array
layout information of the uniform
rectangular array; iteratively calculating the two-dimensional
direction angle set, accuracy vector, and
Gaussian white noise accuracy parameters of the candidate
target signal according to the array manifold matrix learning strategy to obtain the posterior estimate of the candidate
target signal; and using this posterior estimate to calculate the normalized
spatial spectrum value, with the two-dimensional
direction angle corresponding to the maximum value being the target
azimuth estimate. The number of two-dimensional direction angles in this invention increases sequentially from zero, resulting in a lower number of columns in the array manifold matrix and reducing the complexity of parameter iteration calculation. Furthermore, this invention designs an efficient two-dimensional
direction angle calculation method with
high angle estimation accuracy.