Weapon configuration, allocation and route planning with time windows for multiple unmanned combat air vehicles

Abstract

Unmanned combat air vehicles (UCAVs) mission planning is a fairly complicated global optimum problem. Military attack missions often employ a fleet of UCAVs equipped with weapons to attack a set of known targets. A UCAV can carry different weapons to accomplish different combat missions. Choice of different weapons will have different effects on the final combat effectiveness. This work presents a mixed integer programming model for simultaneous weapon configuration and route planning of UCAVs, which solves the problem optimally using the IBM ILOG CPLEX optimizer for simple missions. This paper develops a heuristic algorithm to handle the medium-scale and large-scale problems. The experiments demonstrate the performance of the heuristic algorithm in solving the medium scale and large scale problems. Moreover, we give suggestions on how to select the most appropriate algorithm to solve different scale problems.

Precise Firing Methods for Small-caliber Unmanned Intelligent Firearms Based on BP Neural Network and Model Predictive Control

“…Image servo tracking accuracy serves as one of the key elements for the firing accuracy of SCUIW, which capture the target through the camera [14] and lock the target through the servo system [15], so the image servo tracking accuracy is one of the key factors affecting the firing accuracy. In a battlefield environment, soldiers and light-armored vehicles are targets for SCUIW.…”