Multiple-input multiple-output array radar staring imaging method based on tensor compression perception

Abstract

The invention belongs to the technical field of radar, and discloses a multiple-input multiple-output array radar staring imaging method based on tensor compression perception. The method includes the steps of configuring a transmit-receive array, setting each emission array element in the emission array to emit random frequency hopping signals, setting the referential array element position coordinate of the array, the transmit-receive array and the coordinates of a target scene, establishing a signal reception model of a radar reception array in a same range gate, matching and filtering the reception data, converting the problem of restoring the scattering coefficient of a single-range gate into solving sparse optimization, reconstructing the target scene in the single-range gate for the sparse optimization of signal reception model by using an improved 2D-SL0 high-efficient rapid imaging method, reconstructing the scattering coefficient matrix in each range gate by using the rapid image reconstruction algorithm, and finally obtaining the multi-range gate target scene image. The algorithm complexity is reduced, the image reconstruction time is shortened, and rapid imaging of non-sparse large scene object is realized.

Description

technical field [0001] The invention relates to the field of radar technology, in particular to a tensor compressed sensing-based multi-transmission and multi-reception array radar staring imaging method, which can be used for rapid imaging of multi-transmission and multi-reception array radar signal models. Background technique [0002] Traditional staring imaging radars generally use real-aperture imaging technology to generate narrow beams to irradiate the target scene through beamforming, and process the received data to obtain the target scene image. As early as 1974, D.D. Howard used monopulse radar to process the three-dimensional image of the target scene. Subsequently, the domestic University of Electronic Science and Technology of China and Shanghai Jiaotong University respectively developed real-aperture imaging radars and put them into use. Real-aperture staring imaging radar is easier to implement and is conducive to real-time imaging, but its azimuth resolutio...

AI Technical Summary

Problems solved by technology

When the target scene is large, this processing method leads to a large dimension of the perception matrix, which increases the storage burden of the computer and the complexity of the compressed sensing reconstruction algorithm

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