High-resolution range profile feature retention enhancement method based on iterative weighted sparse decomposition

By using iterative weighted sparse decomposition technology, adaptively adjusting the singular value weights, and combining the alternating direction multiplier method, the problem of clutter suppression and feature preservation in radar under strong clutter backgrounds is solved, thereby improving the performance and reliability of radar target recognition.

CN121805968AActive Publication Date: 2026-04-07CHINA ELECTRONIC TECH GRP CORP NO 38 RES INST +1
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Patent Information

Application Number
CN202610269106.4
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-03-06
Publication Date
2026-04-07
Estimated Expiration
2046-03-06

AI Technical Summary

Technical Problem

Existing radar technology struggles to effectively suppress clutter interference while maintaining the scattering point structure characteristics of the target's high-resolution range image, leading to a decline in recognition performance.

Method used

An iterative weighted sparse decomposition method is adopted, which adaptively adjusts the singular value weights of the low-rank clutter component matrix and combines the alternating direction multiplier method for iterative solution to construct an optimized model to separate clutter and target components while maintaining the structural features of the high-resolution range image.

Benefits of technology

Under strong clutter conditions, it significantly improves the performance and reliability of radar target identification, maintains the number, location and relative amplitude relationship of scattering points, and provides stable and reliable feature input.

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Abstract

The invention discloses a high-resolution range profile feature retention enhancement method based on iterative weighted sparse decomposition, and the method comprises the steps: obtaining radar echo data collected by a radar receiver within a coherent processing time, and constructing a two-dimensional radar echo matrix composed of a range unit number and a pulse sequence number after range direction matching filtering; representing a two-dimensional radar echo matrix as a superposition relation of adding a low-rank clutter component matrix and a sparse target component matrix; based on the superposition relation, an optimization model is constructed, and the objective function of the optimization model is the sum of the weighted nuclear norm of the low-rank clutter component matrix and the L1 norm of the sparse target component matrix. According to the method provided by the invention, the adaptive weight is applied to the singular value, so that clutters are effectively suppressed under a strong clutter background, and key structure features such as the number, position distribution and relative amplitude relationship of scattering points in the target high-resolution range profile are kept.
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