We provide a new method to simulate the process of tracking the noncooperative object that moves beyond visual range with a photon-counting laser ranging system. Based on fundamentals of photon-counting laser ranging techniques and parameters of the experimental prototype, we generate echo events according to their probability. Then, we accumulate the echo data in a certain period of time and accurately extract the object’s trajectory with mean-shift and random sample consensus algorithms. Depending on the trajectory during the accumulation period, we predict the relative movement of the object in succeeding cycles by using self-tuning α−β filtering and carefully pick out photon echo signals and apply the polynomial fitting to them to compute the trajectory of the object. The simulation shows that the error between the theoretical trajectory and the extracted trajectory is decreasing all the time, which suggests that we can track the object precisely as the time goes by. The simulation in this paper provides a new way for applications like satellite orientation, identification, troubleshooting, etc.