为应对传感器攻击，提出安全防护模块保障飞行控制安全。
Secure Safety Filter: Towards Safe Flight Control under Sensor Attacks
- 通过安全状态重构与控制防护双模块实现抗攻击飞行控制。
- 在存在有界测量噪声的非线性无人机系统中仍保持安全性能。
- 适用于真实硬件实验，对传感器攻击具有强鲁棒性。
现代自动驾驶系统易受传感器攻击，危及飞行安全。为此，本文提出一种模块化解决方案——安全防护滤波器，将成熟的基于控制屏障函数（CBF）的安全滤波器扩展至可应对并缓解传感器攻击。该模块包含安全状态重构器（生成合理状态）和安全滤波器（计算最接近原始指令的安全控制输入）。不同于仅关注线性、无噪声系统的现有方法，所提安全防护滤波器可处理有界测量噪声，并借助降阶模型技术适用于无人机的非线性动力学。软硬件在环仿真及真实无人机实验均验证了其在传感器攻击下保障系统安全的有效性。
原文摘要 · Abstract (English)
Modern autopilot systems are prone to sensor attacks that can jeopardize flight safety. To mitigate this risk, we proposed a modular solution: the secure safety filter, which extends the well-established control barrier function (CBF)-based safety filter to account for, and mitigate, sensor attacks. This module consists of a secure state reconstructor (which generates plausible states) and a safety filter (which computes the safe control input that is closest to the nominal one). Differing from existing work focusing on linear, noise-free systems, the proposed secure safety filter handles bounded measurement noise and, by leveraging reduced-order model techniques, is applicable to the nonlinear dynamics of drones. Software-in-the-loop simulations and drone hardware experiments demonstrate the effectiveness of the secure safety filter in rendering the system safe in the presence of sensor attacks.
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