Autonomous dimensionality reduction navigation method for deep sky object (DSO) landing detector

Abstract

The invention belongs to the technical fields of guidance, navigation and control of a deep sky object (DSO) detector, and particularly discloses an autonomous dimensionality reduction navigation method for a DSO landing detector. The method comprises the following steps of: determining the attitude, position and initial speed value of the detector relative to an inertial coordinate system at the current time; determining the distance of the detector relative to the center of the DSO; determining the three-dimensional (3D) speed of the detector relative to the inertial coordinate system; constructing the state quantity, state equation, observed quantity, observation equation and measurement noise variance matrix of a navigation system; carrying out non-dimensionalization on the measurement noise variance matrix, and determining observability; processing the measurement noise variance matrix, the observation equation, the observed quantity and an observation matrix by a decomposition transformation method; and determining the distance and speed of the detector relative to the center of the DSO by utilizing extended Kalman filtering (EKF) based on UD covariance factorization. By means of the method disclosed by the invention, the stability of autonomous navigation filtering can be ensured, and the convergence speed and estimation accuracy of key navigation parameters can be improved.

Description

technical field [0001] The invention belongs to the technical field of guidance, navigation and control of deep-space probes, and in particular relates to a dimension-reducing autonomous navigation method for landing a deep-space celestial body probe. Background technique [0002] Due to the long distance between deep-space celestial bodies and the earth, it is difficult for ground-based deep space network-based navigation to meet the real-time and precision requirements of the deep-space landing GNC system for detector status. Therefore, autonomous navigation has become a safe and accurate way to land deep A key technology for space probes. The general method used for autonomous navigation of deep-space landing probes is: the altitude obtained by the rangefinder and the velocity of the system obtained by the speedometer are used as observations, and the position and velocity errors of inertial navigation are corrected by using the extended Kalman filter. For this navigatio...

AI Technical Summary

Problems solved by technology

For this navigation method, although all orbital parameters are observable, due to the low observability of some orbital parameters (except the radial two-dimensional position), under the influence of navigation model error and measurement noise characteristics uncertainty , these orbital parameters with low observability not only do not converge, but may also diverge, affecting the stability of the autonomous navigation algorithm and the estimation accuracy of key navigation parameters

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