Information Gathering Based Autonomous Online Patrolling Route Planning for Cooperative Loitering Munition Swarm Using Particle Filtering

With the development of autonomous system, the operational use of loitering munition is shifting from the following of a pre-planned fixed route without communication to smart decision making and collaborative cooperation with sharing information. In this paper, we study the autonomous decision making and cooperative control strategy of online patrolling for a swarm of loitering munition using communication to coordinate their route based on maximizing the information they gathered in the operation region. Taking the non-Gaussian non-linear property of airborne radar seeker into account, we utilized a particle filter based method to evaluate or to predict the information quality of each action candidate. We also implemented a coordinate descent scheme to enable a distributed and scalable swarm decision making. Simulation results show that the proposed method provides a better estimation than baselines without the need for external or centralized decision agent.