Cooperative Integrated Estimation-Guidance for Simultaneous Interception of Moving Targets

TL;DR

This paper introduces a cooperative framework combining estimation and guidance for multiple autonomous vehicles to intercept a moving target, even with limited sensor data, using prescribed-time observers and true proportional navigation.

Contribution

It unifies estimation and guidance in a cooperative architecture with heterogenous sensors, employing prescribed-time observers and true proportional navigation for effective interception.

Findings

Framework successfully intercepts targets in simulations

Achieves convergence of target state estimation within set times

Effective even with limited sensor-equipped vehicles

Abstract

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.