Research On Automatic Parameter Adjustment Algorithm Simulation And Verification Technology Of Fine Guide Sensor

The space astronomical telescope is affected by factors such as the actions of the system internal motion components and the platform attitude controller with vibrations at different frequencies.Therefore,a precision image stabilization system is essential to suppress the line of sight(LOS)vibrations and to improve the stability for the space telescope.In order to acquire star spots and calculate the co-ordinates for the precision image stabilization system,the fine guidance sensor(FGS)is mainly provided with the three key functions: Firstly,the rapid extraction of stars in normal working conditions and the calculation of the star centroid co-ordinates.Secondly,the star centroiding information used to calculate the deviation of LOS and star spots feedback signal in the optical closed-loop system.Thirdly,the extraction of centroid co-ordinates features above multiple star spots and the matches with navigation star library by using the matching algorithm.In this way,the system will obtain the real-time absolute attitude information of the telescope LOS rapidly.To detect the attitude deviation of LOS,the fine guidance sensor needs to provide the relevant analyzing data for the precision image stabilization system,so as to the telescope platform with great efficiency and precision.However,the LOS of telescope pointing to the sky with a large observation field may lead to the brightness and distribution of the star varies widely and random.In different sky areas,the conventional method is to configure the CMOS parameters every time,which results in ordinary real-time performance,large amount of data and inconvenient recording operation,etc.In order to solve the problem,the fine guidance sensor needs the adaptive ability to adjust the orbiting parameters of different sky areas,and stars pointing characteristics flexibly.So,the research concentrating on the design of automatic parameter adjustment algorithm for the fine guidance sensor system is carried out as below:(1)A method for automatic adjustment of parameters and the optimal control algorithm of fine guidance sensor in orbit is proposed in the dissertation combining with the star library,stellar features and the imaging model of the point-spread-function of stars.The adjusting method also bases on the analysis of the star characteristics on the focal plane and detector,the derivation of photo-generated electrons number and the corresponding read-out pixel value with different stars.Theoretical simulation of the imaging effect and the centroid extraction algorithm of the star spots with MATLAB is analyzed,and establish an automatic parameter adjustment model to complete the closed-loop simulation.For the automatic parameter adjustment method with a weight of 1.2Δstar for the interval optimization algorithm of the distribution model of the number of stars,it has obvious advantages in the convergence time and the times of parameter adjustments.The algorithm can complete the parameter control and the number of stars convergence within 1s which meets the system requirement,and the design and implementation feasibility of the automatic parameter adjustment scheme is verified.(2)In the FGS,the working characteristics of CMOS image sensor are analyzed,the true noise value is taken into account to the lower limit of the star signal detecting deduction,and the optimal range of integration time with different magnitudes is calculated To figure out the adjustment effect,the measurement and linear fitting about five related parameters including integration time,PGA Gain,Digital Gain Coarse,Digital Gain Fine and ADC Gain is completed.The curves with parameter and pixel output value is drawn under the condition of uniform incident light,and the parameter adjustment method is designed according to the analysis results.So,the imaging results draws from the radiation characteristics of the stars and the parameters of the optical system.The optimal ranges of gain and integration time are calculated according to the best working characteristics of CMOS image sensor(full-well capacity,noise,photoelectric,etc.).The result of this analysis is used to estimate the limit detection magnitude of the detector and constrain the adjustment range of the integration time and gain.(3)The FPGA platform is constructed and the control modules of image data storage based on FIFO buffer state machine and DDR read-write state machine are built up,and FPGA platform assists with the completion of CMOS image data reception and storage in DDR2.The parameter control algorithm is verified by embedding the adaptive processing and control module in FPGA software.Aiming at the design of fast parameter adjustment algorithm for CMOS image sensor,the CMOS relevant parameters of the fine guidance sensor are logical controlled,and the number of extracted star spots is used as the output signal for the adjustable parameter module.The goal of the parameter adjustment is to make sure the number of star spots in the field of view is stabilized in the proper range,so that the number of available star spots in the image is convergent to the expected range,hence the parameter control module and the detector imaging module is in a controlled feedback system.(4)The system testing and parameter adjustment algorithm verification have been completed.Through the IFOV and FOV test,dark background test,dynamic range and bad pixels test,SNR test,imaging test,star spot detection and parameter adjustment test of the CMOS detector,the function and performance test of the system are completed.Through the field test,the integration time was obtained from 300 ms to400ms,the simulation gain ranged from 2 to 8 times,and the experimental analysis results of the number of star points increased from 2 to 6,which verified the expected effect of simulation parameter adjustment.The comparison results of the MATLAB automatic parameter adjustment algorithm simulation and the actual measurement show that the detecting effect and the simulation results can be identical.The innovation of this dissertation is proposing an parameter adjustment and optimization control algorithm based on FPGA for the fine guide sensor,proposing an interval optimization algorithm of star number distribution model,completing the optimal analysis of the adjustment characteristics and priority of the parameters,completing the closed-loop simulation process verification from star map simulation and valid star spot counting to automatic parameter adjustment.The FPGA hardware platform is built up and the automatic control module on the platform is accomplished,and the independent control scheme with flexible and adjustable parameters is proposed to reduce the fixed parameters,so that the fine guidance sensor is in the process of entirely dynamic automatic control.At last,the feasibility and rationality of the proposed method is verified at different levels with FPGA software and hardware level tests,laboratory tests,and field star imaging and parameter adjustment tests.