Joint Estimation and Control for Multi-Target Passive Monitoring with an Autonomous UAV Agent

TL;DR

This paper presents a novel approach for passive multi-target monitoring using a UAV with radar, integrating joint estimation and control to handle obstacles, false alarms, and non-linear measurements.

Contribution

It introduces a combined estimation and control framework with a model predictive guidance controller for complex multi-target tracking in cluttered environments.

Findings

Effective UAV trajectory planning for multi-target tracking.

Robust handling of false alarms and obstacles.

Improved monitoring accuracy in challenging environments.

Abstract

This work considers the problem of passively monitoring multiple moving targets with a single unmanned aerial vehicle (UAV) agent equipped with a direction-finding radar. This is in general a challenging problem due to the unobservability of the target states, and the highly non-linear measurement process. In addition to these challenges, in this work we also consider: a) environments with multiple obstacles where the targets need to be tracked as they manoeuvre through the obstacles, and b) multiple false-alarm measurements caused by the cluttered environment. To address these challenges we first design a model predictive guidance controller which is used to plan hypothetical target trajectories over a rolling finite planning horizon. We then formulate a joint estimation and control problem where the trajectory of the UAV agent is optimized to achieve optimal multi-target monitoring.