Abstract: Aim at the issues of long recurrence interval, random time of the data, strong clutter interference, and the difficulties of modeling target’s motion in the application of electronic reconnaissance satellite, a novel ship target tracking algorithm based on particle filtering for satellite electronic information is proposed in this paper to solve these ship target surveillance problems. Firstly, the association area of the measurements is selected by using the auto-regressive state transition model to suppress the clutter. Secondly, the measurements with similar electromagnetic characteristics to the ship target are utilized to update the weights of the particles. Finally, resampling is considered to remove the particles with small weights and to improve the tracking accuracy. Experimental results on both simulated and real world data demonstrate that the proposed algorithm can stably track the ship targets under strong clutter interference and has substantial improvements in terms of accuracy and robustness.