Information Fusion Based Research On Opto-electronical Tracking Control On Moving Platform

The opto-electronical tracking system is widely used in the fields of astronomical observation,range measurement,monitoring and search,quantum communication,et al.With the expansion of the application,it is increasingly installed on the moving platforms,such as satelites,airplanes,ships and vehicles.Compared with the ground fixed platform,the shake of the boresight caused by the carrier moving would seriously affect the tracking accuracy,which requires that the system needs a strong inertial stability ability;With the development of equipment and engineering technology,the speed and mobility of the target are also higher,and the system tracking ability is also presented with severe challenges;In addition,the space of the moving platform is relatively narrow,which restricted the application of the sensors with excellent performance but large size.Thereforce,considering that sensor performance and control methods are key factors in promoting accuracy,this dissertation would combine the information fusion technology and control methods,improving the control structure while acquiring more accurate state information from different sources' data,to maximize the system's performance.The tracking accuracy of the opto-electronical tracking system is determined by the inertial stabilization ability and target tracking ability.Since the difference of the factors affecting them,we would study stabilization and tracking separately.For the inertia stability of the moving platform,this dissertation proposes two methods.(1)Inertial stabilization method based on CCD and MEMS accelerometer time-domain fusionFor the relatively large volume and weight of the fiber optic gyro(FOG),it is not suitable for miniaturization applications.It is proposed to use an inexpensive and micro MEMS accelerometer for stabilization.Since MEMS accelerometer is susceptible to interference in low frequency,the low-frequency disturbance suppression ability(DSA)of the double-loop system based on CCD and accelerometer is insufficient.In order to enhance the low-frequency performance,it is proposed that an accelerometer-based disturbance observer is used to transform the medium-frequency performance,while an additional virtual velocity loop is to exchange the medium-frequency DSA for the low-frequency DSA.The platform's velocity in the virtual loop is acquired by the acceleration integration and corrected by CCD(the method is a time-domain fusion essentially).Finally,the low-frequency DSA of the system has been promoted with up to-20 d B,making the MEMS accelerometer been able to substitute the FOG for stabilization.(2)Improved inertial stabilization method with frequency-domain fusion-based complementary filteringSince the disturbance extracted by the MEMS accelerometer-based disturbance observer is not accurate and the velocity acquired by time-domain fusion has a serious phase delay in high frequency,the DSA of the system still has room to rise.In order to maximum the DSA,it is proposed to acquire more accurate information of the platform.Considering that CCD is good at low-frequency measurement and the MEMS accelerometer is good at high-freqeuncy measurement,this dissertation proposes a frequency-domain fusion method based on the modified complementary filter,which could choose sensors' specific frequency-band information to fuse as needed,without requiring filters fully complementary.The more accurate acceleration and velocity is used to build the acceleration disturbance observer and the virtual velocity loop.Compared with the time-domain fusion,this proposed method could make the DSA of the platform continueously increase about-10 d B below 30 Hz.For the target tracking of the moving platform,this dissertation proposes two methods.(1)The compound feedforward method based on the fusion of missing distance and the output of the platform's modelIn the moving platform,the traditional feedforward structure fuses the missing disturbance and the integration of the gyro's data to get the inertial position of the target,which only could promote the tracking ability and has a high demand for gyro.The proposed method which fuses the missing distance and the model's output could get the relative motion between the target and the boresight,which simultaneously contains the information of the target and disturbance in inertial space.The proposed structure is essentially a combination of tracking feedforward and disturbance feedforward,which would help to promote both the tracking ability and DSA.Since the fusion model adopts the closed-loop model of the platform,its robustness is good.Morever,as the transfer function of the closed-loop model is 1,the model doesn't need to be identified and it is easy to be implemented in engineering.The experiment proved that compared with the traditional feedforward method,the proposed method has an approximate tracking ability,but additionally has an apparent promotion for the DSA.(2)The improved Smith predictor method based on the fusion of missing distance and the output of the platform's modelSince the compound feedforward method of Chapter 5 couldn't increase the system's bandwidth and has an apparent promotion only in very low frequency,an improved Smith predictor method based on the fusion of missing distance and the output of the platform's model is proposed.It is analyzed that the Smith predictor commonly used to promote the bandwidth and accuracy of a system is essentially a structure which combines the miss distance and the model's output to extract the information of the target and disturbance.Compared with the proposed compound feedforward structure of chapter 5,the difference of the Smith predictor makes the fusion structure change from the feedforward branch to the main path.In order to futher improve the bandwidth and accuracy while maintaining robustness,this paper proposes to adopt a closed-loop model as the reference model,and continueously add a feedforward branch into the main path to reform the transfer characteristics.Experments confirmed that compared with the traditional Smith predictor,the improved one could make the tracking error suppression bandwidth increase from less than 3Hz to 5Hz,and the tracking ability and DSA increase about-5d B in low frequency.Finally,the combination of the improved Smith predictor and the compound feedforward method is attempted to be applied in the system,which complements the two and further promotes the system performance.