Direction of arrival angle estimation method based on Sparse Bayesian learning

Abstract

The invention discloses a direction of arrival angle estimation method based on Sparse Bayesian learning. The direction of arrival angle estimation method mainly solves the problems in the prior art that the computation burden is heavy, the performance of the coherent signal source process is poor, and the errors in the passive location estimation are big. The direction of arrival angle estimation method comprises the following steps: (1) using an antenna receiver to form a uniform linear array, and sampling space signals to obtain observation data, (2) converting the observation data into real values and calculating a covariance matrix, (3) carrying out the mesh generation on airspace, and constructing a real value over-complete base, (4) establishing a sparse matrix equation according to the sparse presentation relationship of the covariance matrix and the over-complete base, (5) obtaining a most sparse solution of an unknown matrix variance through solving a matrix equation by employing the Sparse Bayesian learning, (6) drawing an amplitude spectrogram based on the one-to-one corresponding relation between the spares solution and the space angle, and obtaining the direction of arrival angle degree. According to the direction of arrival angle estimation method, the passive direction-determination calculating speed and the estimation performance on the signal direction angle when in fast and low number of beats are improved. The direction of arrival angle estimation method is applicable to the target reconnaissance and the passive direction-determination.

Description

technical field [0001] The invention belongs to the technical field of signal processing, in particular to a direction-of-arrival estimation method based on a uniform linear array, which can be used for target reconnaissance and passive positioning. Background technique [0002] Signal DOA estimation is an important branch in the field of array signal processing. It refers to the use of antenna arrays to sense and receive space signals, and then use modern signal processing methods to quickly and accurately estimate the direction of the signal source. In radar, Sonar, wireless communication and other fields have important application value. With the continuous advancement of science and technology, there are increasingly higher requirements for the accuracy and resolution of signal direction of arrival estimation. [0003] At present, super-resolution DOA estimation techniques mainly include subspace methods and methods based on sparse representation. Subspace methods such...

AI Technical Summary

Problems solved by technology

Among them, the greedy algorithm has a large drop in estimation performance in the case of low SNR, which can no longer meet the engineering requirements; while the convex optimization method has a very slow operation speed, and in the case of low SNR, the estimation accuracy is not ideal, and the performance against coherent signals is not good. powerful

In practical applications, both target reconnaissance and passive positioning need to be carried out on the basis of angle estimation. The defects in the above algorithms will cause the shortcomings of slow response speed and large estimation errors in target reconnaissance and passive positioning.

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