Comprehensive Performance Evaluation And Software System Design And Implementation Of Deep Space Exploration Navigation System

The field of deep space exploration has gradually become the direction of the world’s major powers in the contemporary era.With the improvement of the level of science and technology and the increasing number of survey tasks,traditional ground navigation methods have been difficult to meet high-precision navigation requirements.The deep space exploration in this project uses the astronomical angular auto-navigation technology because the navigation technology has the characteristics of low delay,autonomy,and high navigation accuracy compared with traditional navigation technology.At the same time,because the filtering algorithm has also played a key role in the autonomous navigation of the detector,it can optimize the navigation data and improve the navigation accuracy.Therefore,it is necessary to carry out an assessment of the navigation system and filtering performance.It can helps to select the optimal filtering method for the navigation system based on the evaluation results.The main research background of this dissertation is the Mars exploration in deep space exploration.Design and implement a navigation assessment system according to the project requirements,evaluate the filtering algorithms such as EKF,UPF,UKF used in the navigation system,and display the generated assessment data visually through the interface,and then compare the performance differences of the navigation filtering algorithms that evaluated by the comprehensive assessment method.The main research results of this dissertation are as follows:1.The characteristics,principles and error analysis of autonomic autonomous navigation were studied.The system state equations of the detector and the measurement equations of the navigation system were analyzed.2.Established basic performance index system and mathematical model for navigation system.Deep space probe sampling point data is calculated by the mathematical model and then comprehensively evaluated by the fuzzy gray clustering method.The method is characterized by adopting fuzzy comprehensive evaluation to fill in the defects of the single-use grey theory and improve the accuracy of the assessment results.The evaluation results show that this assessment model can provide a more accurate,reasonable and comprehensive assessment of the filtering algorithm.3.Aiming at the project background,a navigation assessment system was designed and implemented according to the proposed overall design scheme.The system was developed using the Qt framework.It mainly implements receiving navigation filtering data,and evaluates the navigation system performance indicators through the background index evaluation algorithm,display the generated assessment data visually through the interface.It provides a simple tool to facilitate the viewing and analysis of the performance curve of different filtering algorithms,also support the data import function for data playback.4.Based on the orbit parameters of the real Mars probe,the data of the cruising section of the probe is transmitted to the navigation assessment system for evaluation.At present,three filtering methods are selected for evaluation: EKF,UKF,and UPF.The curves of various indicators are displayed in the evaluation interface.After a comprehensive assessment based on the fuzzy grey clustering assessment method,the UPF navigation results are the best,followed by the UKF,and the EKF is the worst.