Inertia/astronomical integrated navigation method based on residual compensation multi-rate CKF

A technology of integrated navigation and integrated navigation system, applied in the field of inertial/astronomical integrated navigation based on residual compensation multi-rate CKF, which can solve the problems of star sensor output signal delay and low output frequency

Active Publication Date: 2020-05-15
SOUTHEAST UNIV
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Problems solved by technology

[0004] The present invention is oriented to the technical requirements of navigation and positioning of high-speed missile-borne aircraft, in order to solve the problems of star sensor output signal hysteresis and low output frequency, and improve the accuracy of attitude measurement in INS / CNS integrated navigation, a multi-rate volumetric Calculator based on residual compensation is proposed. The inertial / astronomical integrated navigation method of Mann filter (Cubature kalman filter, CKF) can be used in high-speed missile-borne aircraft integrated navigation in high-dynamic environments, etc., effectively improving the autonomy of navigation and positioning, thereby improving navigation accuracy

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[0094] The technical solutions provided by the present invention will be described in detail below in conjunction with specific embodiments. It should be understood that the following specific embodiments are only used to illustrate the present invention and not to limit the scope of the present invention.

[0095] The present invention introduces two types of deep learning mechanisms in the INS / CNS combined system: multi-scale regression (Scale-Recurrent Network, SRN) and Long Short-TermMemory (LSTM) to star sensor image and output frequency optimization. The SRN network realizes the de-blurring of the "tailing" star map, and improves the accuracy of star map centroid extraction. As the sub-module of the filter, the LSTM network expands the system observations, increases the output frequency of CNS, and makes CNS and INS output at the same frequency. The multi-rate volume Kalman filter based on residual compensation realizes the synchronization between INS and CNS data output o...

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Abstract

The invention provides an inertia / astronomical integrated navigation method based on residual compensation multi-rate CKF, and the method comprises the steps: firstly building a state and measurementequation of an integrated navigation system, and recording the state quantity of the system; carrying out deblurring processing on the trailing star map by utilizing an SRN-based image deblurring method; taking the deblurred attitude information as a part of observed quantity of volume Kalman filtering based on residual compensation, and jointly inputting the deblurred attitude information and recorded system state quantity into a filter for filtering estimation; correcting the output delay of the star sensor through residual compensation to realize data synchronization; introducing a long-short-term memory neural network estimator into a multi-rate cubature Kalman filter based on residual compensation to serve as a filter sub-module, and achieving same-frequency output of an inertial sensor and a star sensor. And the optimal estimation of the inertial / astronomical integrated navigation attitude is realized based on the compensated data and model. According to the invention, the autonomy of navigation and positioning can be effectively improved, and the navigation precision is further improved.

Description

Technical field [0001] The present invention relates to the field of inertial navigation technology and deep learning, and relates to an inertial / celestial integrated navigation method based on residual compensation multi-rate CKF. Background technique [0002] As the main sensor used in the Celestial Navigation System (CNS), the star sensor has the advantages of small size, high measurement accuracy, and measurement error does not accumulate over time, but the instantaneous output frequency is low, and the output has a certain delay. Inertial Navigation System (INS) has the characteristics of all-day autonomy and high short-term accuracy. But under its long endurance conditions, the measurement error will diverge over time, and the navigation accuracy will be greatly reduced, which cannot meet the user's requirements for system positioning accuracy. The INS / CNS integrated navigation system can overcome the shortcomings of the two working separately, improve the accuracy and rel...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01C21/02G01C21/16G06N3/04G06N3/08
CPCG01C21/02G01C21/165G06N3/08G06N3/044G06N3/045
Inventor 陈熙源张雨柳笛方琳
Owner SOUTHEAST UNIV
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