Research On XPNAV/CNS Navigation Method Based On Adaptive Filtering

With the continuous development of China’s space technology,the number of China’s orbiting spacecrafts has been increasing.The amount of information spacecraft transfer to the ground has increased sharply.When the spacecraft is in a higher orbit or deep Empty detection,the distance of the spacecraft and ground monitoring and control equipment is too long so that the spacecraft can not rely on the ground station for the calculation of the track.In order to reduce the dependence of the spacecraft on the ground equipment,autonomous running capacity has become the main direction of development of contemporary spacecraft,in which autonomous navigation technology is the premise and core of spacecraft autonomous operation.In order to improve the autonomous navigation capability of spacecraft,this paper designs a set of self-autonomous navigation system consists XPNAV and CNS with high independence,high precision and high reliability.The influence of the disturbance of the spacecraft in the outer space operation is uncertain.This kind of uncertain disturbance express as the randomness and uncertainty of the statistical characteristics of the system noise in the navigation filter.This characteristic of the system noise in the traditional Kalman filter will cause the filtering error to increase or even diverge.Aiming at this problem,a new process noise scaling algorithm based on information covariance matching is proposed in this paper.Without the use of artificial or empirical parameters,the proposed adaptive mechanism has the ability to independently adjust the process noise covariance matrix Q to the best amplitude.The simulation results show that the accuracy of the algorithm is 80% higher than that of the EKF and 25% higher than that of the UKF algorithm..And the adaptive performance of the system noise is good.X-ray pulsar navigation is a new kind of highly autonomous astronomical navigation technology.Its reliable,stable and anti-interference ability is strong.In the orbit of the maneuver because of its longer filter cycle,the accuracy of the loss is more serious,it can not be alone as a means of navigation spacecraft.Aiming at this problem,the traditional navigation system has a short observation time and can provide the advantages of continuous navigation information.Based on the improved adaptive filtering algorithm and the federal Kalman filter,the two navigation methods are combined to give the integrated navigation system framework.And dynamically adjusts the information factors according to the difference between the accuracy and the reliability of the two navigation filters to improve the adaptability of the integrated navigation.The simulation results show that,compared with the single navigation system,the adaptive navigation system has higher filtering precision and no fluctuation in the navigation error when the spacecraft is moving.Compared with the single pulsar navigation,the integrated navigation has a higher robustness.