Among the laser powered unmanned aerial vehicles (UAVs), the method of laser tracking and aiming at the photovoltaic panels of the UAV has become one of the hotspots. In this paper, a particle filter algorithm based on improved butterfly optimization is proposed to solve the problem of large tracking deviation of laser tracking and aiming UAV. Firstly, an adversarial learning strategy is introduced in the initialization stage of the butterfly optimization algorithm, which improves the algorithm optimization performance. Secondly, the position update formula of the butterfly optimization algorithm is optimized to improve the algorithm optimization speed. Finally, the particle filter algorithm introduced by the butterfly optimization algorithm is applied to the tracking and aiming of the laser powered UAV to realize the optimal tracking of the UAV photovoltaic panel by the laser. MATLAB results show that the particle filter algorithm based on the improved butterfly optimization can improve the accuracy of the laser emitted by the laser during the laser tracking and aiming process, effectively reduce the tracking and aiming error, and improve the effect of laser tracking and aiming at the photovoltaic panel of the UAV.