Aiming at the problem of standard PSO algorithm easy to converge at the end stage of optimization process, the paper proposed an advanced particle swarm optimization (PSO) for parameter estimation of marine induction propulsion motor in electric propulsion unmanned submarine. The advanced PSO modified the learning coefficients so as to improve the global search capability in the early stage of the optimization process, and then converged particles to the global optimum at the end stage. The advanced PSO algorithm used the difference between the measurements of the dqaxis currents of induction propulsion motor and the estimation currents of electrical model as the objective function. Estimated parameters comparison of induction propulsion motor among the advanced PSO algorithm, the standard PSO algorithm and genetic algorithm show that the advanced PSO algorithm can get more accurate estimated parameters of induction propulsion motor.