A Novel Numerical Perspective on Estimating the Mission Reliability of Unmanned Aerial Vehicle Swarm in Multi-Phase

Abstract

The mission reliability of unmanned aerial vehicle (UAV) swarm can comprehensively quantify its capability of completing the assigned mission in the specified conditions, which is significant in decision planning and mission success rate improvement. The current swarm mission reliability estimation based on consecutive k-out-of-n: F system is mainly performed by the analytical method, which includes a complicated analysis process and greatly depends on the formation form of UAV swarm. In this paper, a novel numerical perspective on estimating the swarm mission reliability estimation is established, in which an auxiliary random variable is introduced to periodically express the practical single UAV state and then the state of entire UAV swarm can be further simulated. By the employment of numerous UAV swarm state simulations, a Monte Carlo Simulation (MCS) based method is innovatively proposed to numerically estimate the swarm mission reliability based on consecutive k-out-of-n: F system in the conditions of single and multiple phases. Benefiting from the wide adaptability of MCS, the proposed method can be uniformly applicable to the mission reliability analysis of UAV swarm with various formations such as the linear and polygonal swarm formations which are also typically analyzed in this paper. The accuracy and rationality of the proposed method are demonstrated by examples in the linear and polygonal swarm formations.

Keywords: UAV swarm, Mission reliability, Multiple phased mission system, Consecutive k-out-of-n: F system, Numerical Simulation