Particle Swarm Optimized Matched Tracking Algorithm for Power Line Channel Parameter Identification

To improve the identification accuracy of multipath model parameters of low-voltage power line channel and reduce the identification time, a hybrid PSO-MP algorithm is proposed by integrating particle swarm optimization algorithm and matching tracking algorithm, and the problem of identifying parameters of low-voltage power line channel model is investigated by using this method. The results show that the PSO-MP hybrid algorithm integrates the complementary advantages of the two, and the channel parameter recognition accuracy based on the hybrid algorithm is higher than that of the genetic algorithm, PSO algorithm, and genetic matching tracking algorithm, respectively, and the accuracy will be improved with the increase of the number of paths; at the same time, the PSO-MP hybrid algorithm not only improves the channel model parameter recognition accuracy but also improves the convergence speed of the system. It can be seen that the low-voltage power line multipath model parameter identification method based on the PSO-MP hybrid algorithm is feasible and efficient.