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In order to solve the problems of tracking accuracy and servo performance degradation caused by the lagging measurement information and amplitude mismatch of the heterogenous sensor in the photoelectric pod system, a high-precision comprehensive processing method based on multisource sensor measurement information is proposed in this paper according to the typical control loop of the photoelectric tracking system. Firstly, based on the optimal estimation theory, the output miss distance of the tracker is pre estimated to solve the problem of insufficient estimation of target position accuracy and high speed noise. Then, in view of the information mismatch between the angle sensor and the angular velocity sensor, the nonlinear tracking differentiator is used to get the angular velocity of the angle sensor and make a difference with the measured value of the angular velocity sensor. Finally, the amplitude and delay of the measurement information are adjusted adaptively according to the size of the root mean square of the difference value until the difference value is minimized. The algorithm was applied to the stable tracking experiment of a certain type of pod, and the results showed that the tracking accuracy increased from $92\ \mu \text{rad}$ to $54\ \mu \text{rad}$ , which significantly improved the tracking accuracy of the system and proved the effectiveness of the algorithm. The method proposed in this paper can be quickly applied to other photoelectric systems, and has reference significance[1].

In order to solve the problem that friction, wire-wound, wind resistance and other disturbing moments seriously affect the stability tracking precision during the task of the photoelectric pod system, the fuzzy adaptive control algorithm with extended dimension is proposed in this paper. In this method, an accelerometer is first installed on the reflector of the pod. After obtaining the linear acceleration information and transforming it into angular acceleration, the fuzzy adaptive controller is designed according to the characteristics of wind resistance pulsation torque. The controller takes the mirror angular velocity, angular acceleration and target miss distance as input, and further adjusts the output of the controller according to the change of input and the fuzzy rule base of training. This algorithm was applied to the stable tracking experiment of a certain type of pod, and the results show that the tracking accuracy is improved from $59.7\mu\text{rad}$ to $32.4\ \mu\text{rad}$ . It is proved that the algorithm proposed in this paper can effectively suppress the disturbance torque and significantly improve the tracking accuracy and speed stability in the process of pod mission. This algorithm can be used in other servo control systems as a general method of disturbance torque suppression.