Satellite Selection Algorithm Based on Hybrid BFO-PSO
Aiming at solving the problem that the traditional particle swarm optimization(PSO)algorithm is easy to fall into the local optimum in satellite selection,the bacterial foraging optimization(BFO)algorithm is introduced to improve the PSO.Then,a satellite selection algorithm based on hybrid BFO-PSO is proposed.Firstly,by intro-ducing the chemotactic and migration operation of BFO,the local search ability and the possibility of jumping out of the local optimal of PSO can be improved.Besides,a satellite contribution operator is also proposed.After selec-ting the optimal satellite combination with a given number based on BFO-PSO,the number of combined satellites can be gradually increased by calculating the contribution operator of the remaining satellites.With the operator,the number of matrix inversion operations of geometric dilution of precision(GDOP)can be reduced,which will improve the calculation speed.Finally,the validity of the proposed approach is illustrated by the simulation based on the collected GPS data in practice.
万方数据
维普
