This paper proposes an integrated sensing, navigation, and communication (ISNC) framework for safeguarding unmanned aerial vehicle (UAV)-enabled wireless networks against a mobile eavesdropping UAV (E-UAV). To cope with the mobility of the E-UAV, the proposed framework advocates the dual use of artificial noise transmitted by the information UAV (I-UAV) for simultaneous jamming and sensing to facilitate navigation and secure communication. In particular, the I-UAV communicates with legitimate downlink ground users, while avoiding potential information leakage by emitting jamming signals, and estimates the state of the E-UAV with an extended Kalman filter based on the backscattered jamming signals. Exploiting the estimated state of the E-UAV in the previous time slot, the I-UAV determines its flight planning strategy, predicts the wiretap channel, and designs its communication resource allocation policy for the next time slot. To circumvent the severe coupling between these three tasks, a divide-and-conquer approach is adopted. The online navigation design has the objective to minimize the distance between the I-UAV and a pre-defined destination point considering kinematic and geometric constraints. Subsequently, given the predicted wiretap channel, the robust resource allocation design is formulated as an optimization problem to achieve the optimal trade-off between sensing and communication in the next time slot, while taking into account the wiretap channel prediction error and the quality-of-service (QoS) requirements of secure communication. Simulation results demonstrate the superior performance of the proposed design compared with baseline schemes and validate the benefits of integrating sensing and navigation into secure UAV communication systems.

翻译：本文提出一种集成感知、导航与通信（ISNC）框架，用于保护存在移动窃听无人机（E-UAV）的无人机使能无线网络。为应对E-UAV的移动性，所提框架倡导由信息无人机（I-UAV）发射的人工噪声实现双重用途：同时进行干扰与感知，以辅助导航和安全通信。具体而言，I-UAV与合法下行地面用户通信时，通过发射干扰信号避免潜在信息泄露，并基于扩展卡尔曼滤波器利用后向散射的干扰信号估计E-UAV的状态。利用前一时刻估计的E-UAV状态，I-UAV确定其飞行规划策略，预测窃听信道，并设计下一时刻的通信资源分配策略。为规避这三个任务间的强耦合，采用分治方法。在线导航设计以在考虑运动学和几何约束下，最小化I-UAV与预设目标点之间的距离为目标。随后，基于预测的窃听信道，将鲁棒资源分配设计建模为优化问题，以在考虑窃听信道预测误差和安全通信服务质量（QoS）要求的同时，实现下一时刻感知与通信之间的最优权衡。仿真结果表明，所提设计相较于基线方案具有优越性能，并验证了将感知与导航集成到安全无人机通信系统中的优势。