An Evaluation Method for Autonomous Navigation Filtering Algorithms for Deep Space Exploration

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: 2017-03-01
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

But in most cases, we don't have access to actual flight tests, so this method is rarely used

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  • An Evaluation Method for Autonomous Navigation Filtering Algorithms for Deep Space Exploration
  • An Evaluation Method for Autonomous Navigation Filtering Algorithms for Deep Space Exploration
  • An Evaluation Method for Autonomous Navigation Filtering Algorithms for Deep Space Exploration

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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 a method for evaluating autonomous navigation filter algorithms for deep space exploration. Firstly, three navigation filter algorithms of EKF, UKF and UPF are used to process the acquired navigation data, respectively, and the accuracy under the corresponding navigation filter algorithms is respectively obtained. , Usability, continuity, real-time, stability and other performance parameters, the comprehensive evaluation module combines the evaluation values ​​of performance parameters to evaluate the deep space exploration autonomous navigation filter algorithm, so that the comprehensive evaluation module can not only scientifically and accurately It can accurately assign the relative weights among various performance parameters, and it can also accurately evaluate the autonomous navigation filtering algorithm of deep space exploration, which is suitable for the development needs of today's 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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Patent Type & Authority Patents(China)
IPC IPC(8): G06F19/00G01C25/00G01C21/20G01C21/24
Inventor 唐鹏李健唐忠樑贺威赵光琼
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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