Abstract:

To better detect, identify, and track air floating ball, considering the high correlation between the movement of air floating ball and environmental winds, a method that integrates radar detection and positioning, wind field inversion technology to predict the trajectory of air floating ball and determine their payloads is proposed. Based on the current mainstream velocity plane processing method, a dual-volume unit wind field inversion scheme is introduced. In the scheme, a dynamic model with the analysis of aerodynamics for air floating ball is established to predict their trajectories in the air. Additionally, the trajectory degree of inertia （DOI） and mass resistance ratio are introduced to calculate the difference between the theoretical and actual trajectories of air floating ball in an unloaded state, thereby analyzing their inherent aerial attributes and payload conditions. The proposed method is verified by simulation experiments. The results show that the mean absolute error of wind field inversion is below 0.1. The trajectory prediction error is less than 0.162 and it also shows a good robustness with the random observation error. The DOI value can effectively judge the existence of the payload of air floating ball, and the judgment result is less affected by the wind field observation error. Compared to the unloaded state, a 16-fold increase in DOI values with a 1% increase in payload mass. DOI can better display the mass distribution relationship between the air floating ball and the load, when the payload mass accounts for more than 7%, the DOI criterion is more effective. At the same time, the DOI value can be used to judge whether the air floating ball has independent power. From the simulation results, it can be considered that the DOI values greater than 202 indicates that the air floating ball may have autonomous power.

Key words: air floating ball, trajectory prediction, payload recognition, wind field inversion, trajectory degree of inertia (DOI)