A Sparse Direction of Arrival Angle Estimation Method Based on Multiple Transmitter and Multiple Receiver Arrays

Abstract

The invention belongs to the field of array signal processing, and particularly relates to a sparse direction of arrival angle estimation method based on a multiple-input multiple-output array. The method comprises the following steps of s1, establishing a signal model; S2, estimating and vectorizing a signal covariance matrix; S3, expanding the spatial degree of freedom by using a co-prime matrixprocessing method; S4, obtaining target direction of arrival estimation by adopting a neighbor operator method; and S5, determining a target direction of arrival and number. The method disclosed by the invention has the following beneficial effects that the multi-target angle estimation precision under the conditions of low signal-to-noise ratio and small samples can be improved, and method for estimating the target angle is fast in iterative rate of convergence, and high in operation efficiency, can be applied to a real-time multi-target angle estimation system, and has important engineeringapplication value.

Description

technical field [0001] The invention belongs to the field of array signal processing, and in particular relates to a sparse DOA angle estimation method based on a Multiple Input Multiple Output (MIMO) array. Background technique [0002] Direction of Arrival Estimation (DOAE) is a very important problem in the field of array signal processing, and related algorithms can be widely used in radar detection, sonar navigation, multi-channel communication and other fields. Most of the traditional target angle estimation algorithms are based on subspace signal flow analysis or belong to the maximum likelihood estimation algorithm. However, these two types of algorithms often have limited resolution and are greatly affected by factors such as the correlation between target signals, the number of samples collected, and the signal-to-noise ratio of the system, so it is difficult to adapt to various complex application environments in practice. [0003] With the introduction of the sp...

AI Technical Summary

Problems solved by technology

[0007] The technical problem to be solved by the present invention is that the traditional sparse recovery method cannot utilize multiple sets of transmitted signals of the MIMO array, resulting in a loss in the estimation accuracy of the direction of arrival angle. It is difficult to meet the actual estimation accuracy requirements of engineering

Images