Research on real-time route planning for unmanned aircraft in geomagnetic matching guidance

A method of real-time route planning is researched for unmanned aircraft (UA) in geomagnetic matching guidance. Borrow ideas from particle swarm optimization (PSO) algorithm, a two-subpopulation particle swarm optimization (TSPSO) algorithm is proposed to track the changeable environment factor. Methods including route node extension and fitness function calculation are used to design the real-time route planning algorithm. Simulation experiments have been done in three conditions. Result indicates that the real-time route planning method designed in this paper can track changes of the environment factor to replan a new route in time.