Collaborative Multi-MSA Multi-Target Tracking and Surveillance: a Divide & Conquer Method Using Region Allocation Trees

Stability Analysis of Multi-Agent Tracking Systems with Quasi-Cyclic Switching Topologies

In this paper, the stability problem of a class of multi-agent tracking systems with quasi-cyclic switching topologies is investigated. The existing results of systems with switching topologies are usually achieved based on the assumption that the piecewise constant communication topologies are connected and the switchings are cyclic. The communication topologies are possible to be unconnected and it is difficult to guarantee the topologies switch circularly. The piecewise unconnected topology makes the interactive multi-agent tracking system to be an unstable subsystem over this time interval. In order to relax the assumption constraint, a quasi-cyclic method is proposed, which allows the topologies of multi-agent systems to switch in a less conservative way. Moreover, the stability of the tracking system with the existence of unstable subsystems is analyzed based on switched control theory. It is obtained that the convergence rate is affected by the maximum dwell time of unstable subsystems. Finally, a numerical example is provided to demonstrate the effectiveness of the theoretical results.

Resilience evaluation for UAV swarm performing joint reconnaissance mission

The resilience of unmanned aerial vehicle (UAV) swarm is its joint capability to resist possible threat, adapt to disruptive events, and restore its intended performance under a specific time period. The quantitative assessment of the UAV swarm resilience requires a thorough understanding of its missions. In this paper, a mission-oriented framework is proposed to implement the resilience evaluation for the UAV swarm. Guided by the framework, the resilience evaluation for the UAV swarm performing joint reconnaissance mission is studied. A UAV swarm model is developed for joint reconnaissance mission based on complex networks and agent-based models. The following aspects of the UAV swarm are considered in the proposed model, namely, the mission orientation, UAV attributes, swarm topology, UAV cooperative strategy, UAV information exchange and fusion strategy, potential threats, recovery strategies, etc. Then, a novel performance metric is proposed to measure the mission capability of the UAV swarm performing joint reconnaissance mission. Results from the simulations show that, compared with existing studies, the proposed approach can provide more realistic and objective resilience evaluation for the mission-oriented UAV swarm. The above works can be used to support the decision making and the optimal design of the UAV swarm, given different missions.