In view of the complicated low voltage communication environment of distribution network

an unscented Kalman filter (UKF) algorithm is proposed based on ant colony optimization-particle swarm optimization (ACO-PSO) to identify multipath channel transmission model parameters. The UKF algorithm using the minimum mean square error is adopted to estimate the identification effect for the power line multipath channel transmission model. Considering the difficulty in obtaining the optimal filtering effect through test adjustment by the UKF algorithm

this paper proposes an ACO-PSO algorithm based method for optimizing the noise matrix of the UKF algorithm

while introducing the ant colony algorithm in discretizing the inertia weight parameters to improve the searching efficiency of the PSO algorithm and overcome the shortcomings of being prone to premature convergence. Test and simulation results show that identifying the power line channel model with this optimization algorithm can overcome the dispersion of model parameters

improve the fitting accuracy and shorten the identification time.