Tongrun Xing, Yongjun Dai, Xuan Liao, Zhiwen Zhang, Tong Zhou, Longlong Zhang, Tian Jiang · 2026 · arXiv
DOI: 10.48550/arXiv.2610.27585 · open-access PDF
随着认知雷达向一维复杂基带序列的端到端处理发展,深层网络面临严重的敌对威胁,但现有的攻击在实际电子战中遇到双重局限性:跨架构的可转移性低,对物理渠道扭曲的严重脆弱性,从而降低了他们的战术可靠性。
Machine translation (Meta M2M100); the English original follows.
As cognitive radars evolve towards the end-to-end processing of one-dimensional complex baseband sequences, deep networks face severe adversarial threats. However, existing attacks encounter dual limitations in practical electronic warfare: low cross-architecture transferability and severe vulnerability to physical channel distortions, which degrades their tactical reliability. To overcome these bottlenecks, we propose a physical prior-driven Segmented Spatio-Temporal Attack (SSTA). First, a global-local feature decoupling segmentation mechanism interrupts the adversarial gradients' dependence
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