Abstract: The rapid development of new energy and the continuous application of power electronic equipment not only promote the rapid development of the whole power system,but also aggravate the harmonic pollution which affects the power quality. Accurate estimation of harmonics is the precondition for effective solution of harmonic pollution. For the low accuracy,low applicability and weak anti-interference of harmonic estimation in the current power system,an improved Tuna swarm optimization particle filtering algorithm（TSO-PF） is proposed in this paper. First,the Tent chaotic map is introduced to initialize the particle population to make its individual distribution more uniform. Second,spiral foraging and parabolic foraging behaviors of tuna are introduced into the particle filter algorithm,and the optimization ability of tuna optimization algorithm is improved by adding Gaussian perturbation factor and water wave dynamic adaptive factor, which guide the particles to move to the high likelihood region and improve the diversity of particles. Finally,the simulation results of IEEE-14node systems show that the proposed algorithm has better robustness,accuracy and anti-interference ability.