Earth satellite self astronomical navigation method based on self adaptive expansion kalman filtering

Abstract

The method includes steps: building up kinematical equation of earth satellite orbit based on rectangular coordinate system; building up measurement equation based on angular distance of starlight as measuring quantity; building up discrete type extended Kalman filtering equation to determine whether extended Kalman filtering is divergent; using prognostic filtering residual to determine whether extended Kalman filter is divergent; if yes, then the method carries out estimating statistic characteristics of noise; otherwise, carrying out calculation according to standard extended Kalman filtering program. The invention solves issue that divergence of noise filter caused by inaccurate determination of statistic characteristics of noise influences on navigation accuracy. Advantages are: independent, flexible and simple, and high precision. The invention is especially suitable to earth application satellite needed high navigation accuracy in resource, weather areas etc.

Description

technical field [0001] The invention relates to an earth satellite autonomous astronomical navigation method based on self-adaptive extended Kalman filter, which can be used for autonomous navigation and positioning of earth application satellites such as resources, communication, reconnaissance and meteorology. Background technique [0002] The celestial navigation system is a completely autonomous navigation system that does not transmit and exchange information with the outside world and does not depend on ground equipment. It is a positioning and navigation method that uses celestial body information measured by optical sensors to calculate the position of the carrier. The basic principle is to use astrometric information combined with orbital dynamics equations, and use the optimal estimation method to estimate the navigation information such as the position and speed of the spacecraft. That is to say, the celestial navigation method can be divided into three parts, one...

AI Technical Summary

Problems solved by technology

[0006] The technical problem solved by the present invention is: to overcome the traditional extended Kalman filter method, which assumes that system noise and measurement noise are Gaussian white noise, resulting in low precision of the navigation system, and proposes a self-adaptive extended Kalman filter based earth satellite The autonomous celestial navigation method realizes the autonomous celestial navigation of earth satellites by being directly sensitive to the horizon. According to the updated information calculated each time by the adaptive extended Kalman filter, the statistical characteristics of the system noise and measurement noise of the actual model are derived, which overcomes the The noise filter divergence problem caused by inaccurate determination of noise statistical characteristics greatly improves the accuracy and scope of application of the earth navigation system

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