Multi-base multi-UAV cooperative reconnaissance path planning with genetic algorithm

Describing cooperative reconnaissance is crucial for air traffic relating to multiple unmanned aerial vehicles (UAVs) loaded in different bases in an increasingly complex battlefield environment. Compared with the traditional problem that all UAVs took off from just one base, this paper is to address reconnaissance missions, which must be done in partnership among multiple UAVs in different bases. To improve missions’ reliability, residence time in effective detection of enemy radars should be mitigated under the premise of missions completed by UAVs. This paper transforms the minimum residence time into the shortest path combinatorial optimization, and discretizes heading angles. Graph theory is applied to analyze path problems and a global model with numerous constraint conditions can be built. Finally, a valuable reconnaissance path planning can be generated through solving the model with genetic algorithm. Also an application example that eight UAVs in four bases finish reconnaissance missions involving sixty-eight targets is established, and then an optimal solution is got to explain both the feasibility and efficiency of the proposed modularization and algorithm.