Towards Physically Realizable Adversarial Attenuation Patch against SAR Object Detection

TL;DR

This paper introduces a physically realizable adversarial attack method for SAR object detection that balances attack effectiveness with stealthiness, and is suitable for real-world electronic jamming.

Contribution

It proposes the Adversarial Attenuation Patch (AAP), a novel energy-constrained, physically deployable attack framework for SAR systems, advancing beyond digital-only methods.

Findings

AAP effectively degrades detection performance

Maintains high imperceptibility of attacks

Shows strong transferability across models

Abstract

Deep neural networks have demonstrated excellent performance in SAR target detection tasks but remain susceptible to adversarial attacks. Existing SAR-specific attack methods can effectively deceive detectors; however, they often introduce noticeable perturbations and are largely confined to digital domain, neglecting physical implementation constrains for attacking SAR systems. In this paper, a novel Adversarial Attenuation Patch (AAP) method is proposed that employs energy-constrained optimization strategy coupled with an attenuation-based deployment framework to achieve a seamless balance between attack effectiveness and stealthiness. More importantly, AAP exhibits strong potential for physical realization by aligning with signal-level electronic jamming mechanisms. Experimental results show that AAP effectively degrades detection performance while preserving high imperceptibility, and shows favorable transferability across different models. This study provides a physical grounded perspective for adversarial attacks on SAR target detection systems and facilitates the design of more covert and practically deployable attack strategies. The source code is made available at https://github.com/boremycin/SAAP.