Research On Attitude Sensor Based Satellite Autonomous Navigation And Error Calibration Methods

The number of on-orbit satellites is increasing fast with the expansion of application fields in china.Traditional daily management depended on the ground TT&C center has become unsuitable for the demand of development.Therefore,it is necessary to promote the satellite ability of autonomous operation.As the research and application basis of the autonomous operation technology,autonomous navigation is one of the most important research directions of the satellite intelligent and autonomous control.Meanwhile,celestial navigation is a kind of fully autonomous navigation method which has a broad application in satellite for many years.However,the on-orbit performance of celestial navigation is not as satisfactory as expectation.The main problem is that the navigation accuracy is degraded badly by the sensor measurement error.Therefore,this dissertation mainly researches the attitude sensor based satellite autonomous navigation and error calibration methods,which compensate the error caused by the sensor measurement in order to improve the on-orbit accuracy of celestial navigation.The main contributions are as follows:According to the analysis of on-orbit data and precision characteristic,this dissertation concludes the composition and expression of measurement errors for several kinds of celestial sensors.Based on formulations of random noise,constant bias and low-frequency error(LFE),the sensor models including measurement error are established for the simulation setting and the error calibration and compensation on orbit.Further more,an autonomous celestial navigation method with the calibration capability is proposed to determine the satellite orbit parameters in real time by the improved EKF algorithm.The navigation method is suitable for various satellite orbits including LEO,MEO and GEO.An applicable calibration interface is designed to availably compensate the navigation bias error and LFE caused by sensor measurement.The influence of error propagation in navigation filtering process is analyzed to indicate the necessity of calibration.The random noise can be treated by the Kalman filter,but the constant bias and LFE must be calibrated and compensated,otherwise the navigation accuracy will be degraded badly.Therefore,this dissertation proposes a ground calibration method based on the position data.The earth direction vector error is calculated as the calibration input by the ground precise orbit parameters and the navigation positioning results.The coefficients of sensor measurement error can be calibrated by the least square estimation.However,the navigation error is also influenced by other factors such as the system model and filter algorithm.Most of the time,it is impossible to independently identify the measurement error from the positioning result.Therefore,this dissertation proposes another calibration method based on the attitude data.The calibration input is calculated by comparing the attitude determination angles of different sensors.The coefficients which are calibrated from the attitude data can accurately compensate the sensor measurement error without the problem of the position-based method.A relative position data based calibration method is proposed for the navigation based on Hill equation.The calibration input is calculated by the relative longitude and latitude errors both from the ground measurement and the navigation determination.The coefficients can also be calibrated by the least square estimation.The ground calibration methods are proved to be effective by the simulation and application,and can be used in satellite daily management to improve the on-orbit accuracy of celestial navigation.Actually,the sensor measurement error is constantly changing so that a set of calibration coefficients is only valid for a period of time.The ground station has to recalibrate regularly to ensure the compensation accuracy.In order to reduce the workload on the ground and improve the ability of satellite autonomous operation,an on-board calibration method is proposed based on the positioning data of GNSS.The coefficients are calibrated continuously by the recursive least square estimation,and substituted synchronously into the calibration interface of the filter algorithm.The navigation error is calibrated and compensated on-board autonomously.However,it is difficult to obtain the measurement data of at least four navigation satellites at the same time for GEO/HEO.Therefore,a new on-board calibration method is proposed based on the single pseudorange.A self-calibration EKF is designed based on the augmented state vector including the coefficients of constant bias and LFE.Both the satellite orbit parameters and the calibration coefficients can be estimated on-board synchronously.Simulation and application results illustrate the validity of these proposed calibration methods,which can be used to calibrate and compensate the navigation error during the whole life of satellite autonomous operation in order to solve the problem of on-orbit variation of sensor measurement error.The proposed navigation and calibration methods can compensate the navigation error caused by the constant bias and LFE of sensor measurement.The navigation accuracy will be improved in orbit significantly.These methods are beneficial to enhance the independent survival of military satellites and the market competitiveness of civil satellites,and have broad application prospect and important application value.