A video speed measurement method for UAV targeting ground targets based on kalman filtering

Abstract Measuring the velocity information of moving targets, as an application scenario for drone target velocity measurement, is an important focus in the process of drone intelligence reconnaissance. To improve the speed and accuracy of unmanned aerial vehicles (UAVs) in locating and measuring moving targets, a reliable target localization and velocity model based on UAV reconnaissance video frames and Kalman filtering is proposed. This algorithm model can complete the localization and velocity measurement tasks of moving targets under complex conditions without the need to obtain ranging information from drones. To verify the algorithm, the Monte Carlo simulation method was used for simulation experiments. The experimental results show that the error of this velocity measurement algorithm can meet the accuracy requirements of unmanned aerial vehicles for ground-moving targets.