Nested multiple-input multiple-output radar doa estimation method based on compressive sensing

Abstract

The invention discloses a nest multiple-input and multiple-output radar DOA estimating method based on compressed sensing. The implementing process includes the steps that (1), an emitting array and a receiving array of a nest multiple-input and multiple-output radar are determined by using an array element layout form of a nest array; (2), each pulse repetition period of the radar is matched with a filtering echo signal; (3), a covariance matrix matched with filtering output data is vectorized; (4), a matrix reconstruction method and singular value decomposition are adopted for obtaining noise subspace; (5), an L1norm bound term and an L2 norm bound term in a sparse recovery problem are constructed; (6), the target DOA is determined by solving the sparse recovery problem. The freedom degree expansion characteristic and the high resolution characteristic of compressed sensing of the nest array are used at the same time, and the estimating method can be used for accurately positioning targets with the number larger than the total number of virtual array elements through the radar.

Description

technical field [0001] The invention belongs to the technical field of communication, and further relates to a compression sensing-based nested multiple-input multiple-output radar direction-of-arrival (DOA) estimation method in the radar technical field. The invention can be used to realize accurate positioning of targets whose number is more than the total number of multiple-input multiple-output radar virtual array elements. Background technique [0002] Compared with the phased array radar, the multi-input multi-output radar can effectively expand the aperture of the array and improve the degree of freedom, which is conducive to the detection of multiple targets. Existing technologies for multi-input multi-output radar array design mainly focus on the uniform array arrangement, and virtualize multiple equidistant array elements through large-spaced transmitting arrays and small-spaced receiving arrays, thereby improving the system's parameter recognizability. In the DOA...

AI Technical Summary

Problems solved by technology

This method (hereinafter referred to as the L1-L2 method) is suitable for the DOA estimation problem of the underdetermined direction of arrival. The disadvantage is that the solution results are prone to false peaks, which makes it difficult to determine the true orientation of the target.

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