Cooperative Integrated Estimation-Guidance for Simultaneous Interception of Moving Targets

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.

Nonlinear Cooperative Salvo Guidance with Seeker-Limited Interceptors

This paper presents a cooperative guidance strategy for the simultaneous interception of a constant-velocity, non-maneuvering target, addressing the realistic scenario where only a subset of interceptors are equipped with onboard seekers. To overcome the resulting heterogeneity in target observability, a fixed-time distributed observer is employed, enabling seeker-less interceptors to estimate the target state using information from seeker-equipped agents and local neighbors over a directed communication topology. Departing from conventional strategies that approximate time-to-go via linearization or small-angle assumptions, the proposed approach leverages deviated pursuit guidance where the time-to-go expression is exact for such a target. Moreover, a higher-order sliding mode consensus protocol is utilized to establish time-to-go consensus within a finite time. The effectiveness of the proposed guidance and estimation architecture is demonstrated through simulations.