Radio frequency (RF) based systems are increasingly used to detect drones by analyzing their RF signal patterns, converting them into spectrogram images which are processed by object detection models. Existing RF attacks against image based models alter digital features, making over-the-air (OTA) implementation difficult due to the challenge of converting digital perturbations to transmittable waveforms that may introduce synchronization errors and interference, and encounter hardware limitations. We present the first physical attack on RF image based drone detectors, optimizing class-specific universal complex baseband (I/Q) perturbation waveforms that are transmitted alongside legitimate communications. We evaluated the attack using RF recordings and OTA experiments with four types of drones. Our results show that modest, structured I/Q perturbations are compatible with standard RF chains and reliably reduce target drone detection while preserving detection of legitimate drones.

翻译：基于射频的系统正日益广泛地通过分析无人机的射频信号模式来检测无人机，这些信号被转换为频谱图图像，并由目标检测模型进行处理。现有针对基于图像模型的射频攻击主要改变数字特征，但由于难以将数字扰动转换为可传输的波形（这可能引入同步误差和干扰）以及硬件限制，其实现在空中传输方面存在困难。我们首次提出了针对基于射频图像的无人机检测器的物理攻击，该方法优化了特定类别的通用复基带扰动波形，并将其与合法通信信号一同传输。我们利用四种类型无人机的射频记录和空中传输实验评估了该攻击。结果表明，适度且结构化的复基带扰动与标准射频链兼容，并能可靠地降低目标无人机的检测率，同时保持对合法无人机的检测能力。