用噪声测距数据实现无人机围捕与拦截，精度高且稳定。
Aerial Target Encirclement and Interception with Noisy Range Observations
- 通过反同步振动弦轨迹确保目标可观测性
- 状态估计误差指数有界，围捕误差可收敛
- 适合无人机围捕、对抗等实际飞行场景
本文提出一种策略，利用噪声范围观测值对非合作空中点质量目标进行围捕与拦截。该方法中，守护无人机采用反同步（AS）三维‘振动弦’轨迹，确保目标可观测性，基于卡尔曼滤波实现快速位置与速度估计。同时设计新型反目标控制器，使守护无人机能自适应完成从保护目标围捕到敌方目标围捕、拦截与中和的转换，考虑了守护无人机的输入约束。基于保证的均匀可观测性，严格分析了状态估计误差的指数有界稳定性及围捕误差的收敛性。仿真结果与真实无人机实验进一步验证了系统设计的有效性。
原文摘要 · Abstract (English)
This paper proposes a strategy to encircle and intercept a non-cooperative aerial point-mass moving target by leveraging noisy range measurements for state estimation. In this approach, the guardians actively ensure the observability of the target by using an anti-synchronization (AS), 3D ``vibrating string" trajectory, which enables rapid position and velocity estimation based on the Kalman filter. Additionally, a novel anti-target controller is designed for the guardians to enable adaptive transitions from encircling a protected target to encircling, intercepting, and neutralizing a hostile target, taking into consideration the input constraints of the guardians. Based on the guaranteed uniform observability, the exponentially bounded stability of the state estimation error and the convergence of the encirclement error are rigorously analyzed. Simulation results and real-world UAV experiments are presented to further validate the effectiveness of the system design.
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