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A uniform rectangular matrix target direction estimation method based on array manifold matrix learning

ActiveCN117540138Breduce complexityReduce matrix dimensionComputation complexityTarget signal
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.
Owner:NORTHWESTERN POLYTECHNICAL UNIV