Research on cooperative target detection and tracking of unmanned ground vehicles

This paper proposes optimization algorithms based on nonlinear programming to solve the problem of selection, deployment of unmanned ground vehicles (UGV) and tracking in target detection. If the target is static, it is easy to find the nearest UGV nodes as the executors, and obtain their deployment locations by simple numerical calculation. But while the target is in movement, firstly, it is need to predict the trajectory according to the motion state of it. Then choose the most suitable task nodes for detection based on the optimization algorithms by the shortest time or distance, and accomplish the deployment of the nodes and the collaborative detection ultimately. If the detection needs to perform continuously for target tracking, the tracking path follow the target is obtained by continuously calculating the optimal locations of the task nodes. The simulation results show that the shortest time optimization strategy can achieve cross-detection in the shortest time, and continuous tracking of the target. And the shortest distance optimization strategy can be used to achieve interception of the target, which is suitable for close reconnaissance and hunting.