Objective  Photoelectric tracking system (Acquisition, Tracking, and Pointing, ATP) is a kind of equipment that uses photoelectric technology to realize the pointing and tracking of the target. It has the characteristics of high measurement and tracking accuracy. The existing ATP system usually carries precise optical systems and detectors, which can accurately locate, track and aim the target. For high-speed target tracking system, the time delay of sensor feedback such as image becomes the main factor that restricts the upper limit of tracking speed of the system. The delay link of system feedback has become the bottleneck restricting the improvement of ATP system's tracking ability. Therefore, an improved tracking feedforward control method is proposed based on sensor fusion prediction to solve the problem of ATP tracking high-speed targets.

  Methods  Firstly, the CCD and high-precision encoder are fused with sensor data, and the target motion state is tracked according to the differential tracking principle to obtain the high-order information of the target motion, and the noise caused by the difference is greatly reduced. Secondly, a reduced-order CA model is proposed to reduce the computation and estimation parameters, and compensate the pure delay link of miss distance according to the Kalman filter principle to obtain the low-delay target motion state information. Thirdly, the least-squares polynomial fitting is performed only by combining the results of the previous moment, which avoids the problem of ill conditioned matrix in the least-squares, and can greatly reduce the calculation amount of fitting, and realize the expansion of CCD feedback from low frequency signal to high frequency signal. Finally, according to the prediction results and higher-order motion information, a tracking feedforward control loop is designed to improve the response speed and tracking ability of the system.

  Results and Discussions  A new control method for ATP system to track high-speed targets is proposed. The high-order motion information of the target is obtained through sensor fusion, and the Kalman prediction based on the reduced-order CA model is carried out. The input deviation after prediction compensation is shown (Fig.12), and the error is reduced by about 88.22%; Combining the least-squares fitting at the previous moment, the problem of ill conditioned matrix in the least squares is avoided, and the expansion of data signal is realized to ensure the data stability of the system.

  Conclusions  An improved tracking feedforward control method is proposed based on sensor fusion prediction, aiming at the problem that the feedback frame rate of CCD camera in the photoelectric tracking system is low and the delay is large, resulting in poor tracking ability and response ability of high-speed targets. The simulation results and experimental results show that the tracking error caused by image lag can be greatly reduced without changing the closed-loop stability of the control system when tracking high-speed targets. The actual test results show that the tracking error after compensation is about 83.67% less than the tracking error before compensation. This method can more effectively compensate the image delay, improve the system control bandwidth, and provide an effective idea for the high-performance tracking control of ATP system.