Research on Effectiveness Evaluation of Multi-UAV System Based on Improved Information Entropy by Prior Data

Due to the characteristics of multiple random factors and flexible equipment composition, the effectiveness of multi-Unmanned Aerial Vehicle (UAV) system is difficult to evaluate accurately. Based on the modification of prior calculation data, an improved information entropy effectiveness evaluation method which considers the influence of random factors is proposed. First of all, this paper establishes the node model and edge model of the multi-UAV system based on the operation loop, enabling the construction of the network for executing forest firefighting tasks. Then, the prior data are utilized to modify the method of evaluation of information entropy effectiveness under the influence of random factors. Finally, using a forest firefighting scenario as an example, the proposed method is applied to calculate the effectiveness of a multi-UAV system in performing forest firefighting tasks. The influences of random factors, equipment coordination, equipment capabilities and the reasonable arrangement of tasks on the effectiveness of multi-UAV system are, respectively, discussed. The conclusion demonstrates that random factors will lower the success rate of multi-UAV system in performing firefighting tasks. Equipment collaborative connection not only boosts the effectiveness of multi-UAV system by 11.2%, but also alleviates the adverse effects of random factors and equipment performance attenuation on the mission success rate. Moreover, the reasonable arrangement of tasks can effectively enhance the success rate of forest firefighting tasks. It has been verified by numerical examples that the effectiveness evaluation method proposed in this paper has good applicability for multi-UAV system.