多无人机在复杂环境中实现对多个目标的围捕，无需GPS
Distance-based Multiple Non-cooperative Ground Target Encirclement for Complex Environments
- 基于距离测量与卡尔曼滤波估计目标状态
- 双机反同步控制实现对向包围并避障
- 适用于城市峡谷等无GPS场景的实战围捕
本文针对城市峡谷等障碍密集、无GPS环境下的多目标多无人机围捕问题，提出一套完整策略。无人机配备全向测距传感器，可鲁棒检测地面目标并获取含噪相对距离。任务分配后，通过估计测量噪声方差并结合卡尔曼滤波，提出新型距离基目标状态估计算法（DTSE）。利用反同步技术与伪力函数，设计加速度控制器，使两架任务无人机协同从对向位置包围目标，同时避开障碍物。理论证明了该算法对离散时间二阶积分系统在可观测性方面的有效性。仿真结果展示了算法在空地协同场景中的泛化能力，实验验证了方法的有效性。
原文摘要 · Abstract (English)
This paper proposes a comprehensive strategy for complex multi-target-multi-drone encirclement in an obstacle-rich and GPS-denied environment, motivated by practical scenarios such as pursuing vehicles or humans in urban canyons. The drones have omnidirectional range sensors that can robustly detect ground targets and obtain noisy relative distances. After each drone task is assigned, a novel distance-based target state estimator (DTSE) is proposed by estimating the measurement output noise variance and utilizing the Kalman filter. By integrating anti-synchronization techniques and pseudo-force functions, an acceleration controller enables two tasking drones to cooperatively encircle a target from opposing positions while navigating obstacles. The algorithms effectiveness for the discrete-time double-integrator system is established theoretically, particularly regarding observability. Moreover, the versatility of the algorithm is showcased in aerial-to-ground scenarios, supported by compelling simulation results. Experimental validation demonstrates the effectiveness of the proposed approach.
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