The observation equation has to be linearized for the multipath estimation algorithm based on Extended Kalman Filter (EKF).To tackle the problem of being sensitive to initial state

which leads to a performance degradation in terms of estimation accuracy

a new multipath estimation algorithm based on intelligent optimization is proposed.Through minimizing the second moment of the estimation error the multipath estimation problem is transferred into an optimization problem with constrained conditions.Furthermore

the instantaneous error is considered as a constrained condition as well as the prior information of the multipath parameters.Then

an intelligent optimizat

ion algorithm is used to solve the presented optimization problem.Especially

the

ε

Constrained Rank-based Differential Evolution (

ε

CRDE) algorithm is adopted.In addition

the

ε

CRDE algorithm is improved to cater for the need of iteration for multipath estimation.Simulation results show that the proposed algorithm outperforms EKF for multipath estimation in the case of single multipath and two multipaths.