Extended Kalman Predictive Filter and Its Application in Theodolite System

Tracking accuracy and pointing accuracy are the core indicators of photoelectric theodolite, and the speed stationarity in the process of tracking and pointing determines the quality of target image acquisition, affects the parameters acquisition and technical and tactical indicators judgment of the target under test[2]. In order to improve the tracking accuracy, pointing accuracy and speed stability of the photoelectric theodolite in the shooting range, the prediction algorithm based on extended kalman filter (EKF) to compensate the sensor delay and the extraction speed method of the tracking differentiator are proposed in the shooting range maneuvering measurement environment. First, the EKF algorithm is analyzed and the EKF-based pointing model is established. Then, in the velocity loop of the theodolite servo control system, the tracking differentiator is used to process the Angle information of the encoder as velocity feedback[3]. Finally, the method proposed in this paper is introduced into Simulink simulation. The results show that the method in this paper improves the speed stability, tracking and pointing accuracy of the photoelectric theodolite, and meets the application requirements of the range. This method can also be transplanted to other photoelectric equipment[1].