This paper proposes a cooperative integrated estimation-guidance framework for simultaneous interception of a non-maneuvering target using a team of unmanned autonomous vehicles, assuming only a subset of vehicles are equipped with dedicated sensors to measure the target's states. Unlike earlier approaches that focus solely on either estimation or guidance design, the proposed framework unifies both within a cooperative architecture. To circumvent the limitation posed by heterogeneity in target observability, sensorless vehicles estimate the target's state by leveraging information exchanged with neighboring agents over a directed communication topology through a prescribed-time observer. The proposed approach employs true proportional navigation guidance (TPNG), which uses an exact time-to-go formulation and is applicable across a wide spectrum of target motions. Furthermore, prescribed-time observer and controller are employed to achieve convergence to true target's state and consensus in time-to-go within set predefined times, respectively. Simulations demonstrate the effectiveness of the proposed framework under various engagement scenarios.
翻译:本文提出了一种协同集成估计-制导框架,用于利用无人自主车辆编队同时拦截非机动目标,假设仅部分车辆配备专用传感器以测量目标状态。与以往仅关注估计或制导设计的方法不同,所提框架将二者统一于协同架构中。为克服目标可观测性异构性带来的限制,无传感器车辆通过有向通信拓扑与邻近智能体交换信息,并借助预设时间观测器估计目标状态。该方法采用真实比例导引制导(TPNG),其使用精确的剩余飞行时间公式,适用于广泛的目标运动模式。此外,通过预设时间观测器与控制器分别实现目标真实状态的收敛及剩余飞行时间在设定预定义时间内的协同一致。仿真验证了所提框架在不同交战场景下的有效性。