Cooperative Loitering Munition Swarm Online Patrolling Route Planning with Nonlinear Seeker Measurement

With the development of autonomous systems, the operational use of loitering munition is shifting from the following of a preplanned 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 munitions using communication to coordinate their route based on maximizing the information they gathered in the operation region. Taking the non-Gaussian nonlinear 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.