A SAR composite jamming suppression method, device and equipment

By introducing a U-shaped network framework with Swing Transformer and multi-scale feature guidance module, combined with a composite loss function, the problems of insufficient feature discrimination and model dependence in SAR composite interference suppression are solved, achieving efficient and adaptive interference suppression effect.

CN122283609APending Publication Date: 2026-06-26XIDIAN UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
XIDIAN UNIV
Filing Date
2026-03-25
Publication Date
2026-06-26

AI Technical Summary

Technical Problem

Existing SAR interference suppression methods suffer from limitations in feature discrimination or reliance on prior models when facing complex interference. Model-driven methods are insufficient in feature discrimination or rely on prior models, while data-driven methods struggle to uniformly represent complex interference, resulting in limited suppression effectiveness and loss of target signal.

Method used

A U-shaped network framework based on the Swin Transformer module and the multi-scale feature guidance module is adopted, combined with a composite loss function, and SAR echo data is processed through short-time Fourier transform and inverse transform to achieve adaptive suppression of composite interference.

Benefits of technology

It improves the generalization ability under complex interference, completely suppresses interference and reduces the loss of target signal, and enhances the robustness of the model in complex coupled interference scenarios.

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Abstract

This invention provides a method, apparatus, and device for suppressing SAR composite interference. The method includes: acquiring SAR echo data containing interference; performing short-time Fourier transform processing on the interfering SAR echo data to obtain echo time-frequency map data; inputting the echo time-frequency map data into a pre-trained anti-interference model for interference suppression processing to obtain interference-suppressed echo data; processing the interference-suppressed echo data using inverse short-time Fourier transform to obtain a de-interference reconstructed signal; and performing imaging processing on the de-interference reconstructed signal to obtain an interference-suppressed SAR imaging result. The pre-trained anti-interference model is a U-shaped network framework based on a combination of a Swing Transformer module and a multi-scale feature guidance module; the pre-trained anti-interference model is trained using a composite loss function. This significantly reduces target signal loss and enhances the model's robustness in complex coupled interference scenarios.
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