Abstract

In order to solve the problem that particle swarm optimization (PSO) tends to fall into the local optimal solution and the convergence speed is slow when solving multi-sensor resource scheduling model, a cuckoo particle swarm optimization (CPSO) algorithm is proposed on the basis of PSO. On the basis of target tracking model, the multi-sensor scheduling model is established. Then the LEVY flight was introduced from cuckoo algorithm into particle swarm algorithm, the algorithm can jump out of the local optimal solution as soon as possible and improve the convergence speed and accuracy of the algorithm. The simulation results show that the improved algorithm is effectively improved in terms of convergence speed and accuracy, and is applied to the solution of sensor scheduling model to further enhance the optimization ability and achieve good results.

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