A new particle swarm optimizer algorithm and application

Particle swarm optimizer (PSO) is an intelligent algorithm which simulates the hunting activity of the group of birds. It´s very clear, easy-defined, simple-operation and realizable. It can be used in radar-network to solve the program of radar system error. However, PSO is one of probability optimizer with premature phenomenon which makes it impossible for PSO to be guaranteed the global optimization solution to converge. The solutions used now have much shortage, so MV_PSO is introduced with concept of multi-velocity and speed coefficient. Its application to radar-network proves that MV_PSO is useful. Compared with standard PSO, MV_PSO has better global optimal capability with faster evolution speed and higher accuracy. Compared with traditional Gauss-Newton, MV_PSO is clearer and simpler to use