Assessment method for deep space exploration autonomous-navigation filtering algorithm

A technology of autonomous navigation and filtering algorithm, which is applied in the field of deep space exploration and can solve problems such as the inability to use flight tests

Inactive Publication Date: 2015-03-11
UNIV OF ELECTRONIC SCI & TECH OF CHINA
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  • Assessment method for deep space exploration autonomous-navigation filtering algorithm
  • Assessment method for deep space exploration autonomous-navigation filtering algorithm
  • Assessment method for deep space exploration autonomous-navigation filtering algorithm

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[0094] For the convenience of description, the relevant technical terms appearing in the specific implementation are explained first:

[0095] EKF (Extended Kalman Filter): Extended Kalman filter;

[0096] UKF (Unscented Kalman Filter): lossless Kalman filter, unscented Kalman filter or dearomatic Kalman filter;

[0097] UPF (Unscented particle filter): unscented particle filter;

[0098] Since this is an evaluation of the autonomous navigation filtering algorithm for deep space exploration, it is impossible for us to obtain real deep space navigation data. Therefore, we use STK and MATLAB mixed programming to obtain the simulation data Satellite_p and Satellite_v. STK provides the speed and position of the sun, the earth, Mars and its satellites, the target star and the target asteroid. Using MATLAB to simulate the process of astronomical angle measurement navigation, redshift speed measurement navigation and speed measurement and angle measurement combination navigation, we...

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Abstract

The invention discloses an assessment method for a deep space exploration autonomous-navigation filtering algorithm. The method comprises steps as follows: firstly, acquired navigation data are processed with three navigation filtering algorithms, namely, EKF, UKF and UPF navigation filtering algorithms, respectively, assessment values of performance parameter indexes such as precision, availability, continuity, instantaneity, stability and the like under the corresponding navigation filtering algorithms are obtained respectively, and then a comprehensive assessment module assesses the deep space exploration autonomous-navigation filtering algorithm in combination with the assessment values of the performance parameter indexes, so that the comprehensive assessment module can scientifically and precisely allocate the relative weight among the various performance parameter indexes as well as accurately assess the deep space exploration autonomous-navigation filtering algorithm, and the method satisfies the demand of development of the current deep space exploration technology field.

Description

technical field [0001] The invention belongs to the technical field of deep space exploration, and more specifically relates to an evaluation method for autonomous navigation filtering algorithms of deep space exploration. Background technique [0002] Human beings have achieved fruitful results in the field of deep space exploration. The pace of deep space exploration in my country is accelerating. At present, a roadmap for deep space exploration before 2030 has been formulated and completed. It is planned to launch a Mars probe in 2018 and an asteroid probe in 2019. device. [0003] Compared with near-Earth space missions, deep space exploration has the characteristics of long flight distance, many environmental location factors, complex flight procedures, long communication delay between equipment and ground, and high autonomy requirements. Among them, the autonomous navigation capability is crucial to the completion of the mission. In the research and design process of n...

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Application Information

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IPC IPC(8): G06F19/00G01C25/00G01C21/20G01C21/24
Inventor 唐鹏李健唐忠樑贺威赵光琼
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
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