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Co-localization Method Based On Federated Kalman Filter For Lunar Rover Positioning

Posted on:2018-01-07Degree:MasterType:Thesis
Country:ChinaCandidate:S Q TangFull Text:PDF
GTID:2392330515489779Subject:Geodesy and Survey Engineering
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As the only natural satellite of the earth,the moon is about 3.8×105km far from the earth,and it is an ideal springboard for the space exploration.Since the new century,it has become an important goal of the space powers to re-set on the moon,exploit and utilize the lunar resources and establish the lunar base.China as the one of the world's space powers,has been in the implementation of their own lunar exploration program,and China is moving towards a "manned lunar landing" plan step by step.In order to ensure the smooth development of the lunar exploration project,determination of the lunar inspector's position is a very important step,so the determination of the lunar inspector's position is the key technology and difficulty of the whole project.VLBI(Very Long Baseline Interferometry)has been developed for more than 50 years.It has been widely used in deep space exploration with high accuracy,high resolution and multi-purpose.We can calculate the location of the lunar rover by using delay data measured by VLBI stations and geometric positioning model which has been established.As a traditional navigation method,celestial navigation has been successfully used in the navigation of some targets,such as hull,satellite and military weapon equipment.Celestial navigation uses the observation information of the earth,the sun and other natural celestial bodies to determine the position information of the target.High precision and high stability is the basic requirement of the lunar rover position.For lunar rover positioning,VLBI technology has high precision,but due to the external uncontrollable factors,the VLBI sign can't been received by the equipment on the earth,the inherent defects of the easily disturbed have some influences on the stability of the lunar rover positioning.Celestial navigation is not affected by the length of time and distance and can provide the information of the position,attitude and so on,but it has poor accuracy of the short time positioning.When combine VLBI with celestial navigation for lunar rover positioning,the joint positioning can improve the positioning accuracy of the lunar rover.Furthermore,the joint positioning can also guarantee the stability and reliability of the lunar rover positioning.Based on the above background,this paper makes a study on the joint of the VLBI and celestial navigation for lunar rover positioning and uses method of Federated Kalman Filter to calculate the result of the joint positioning.The main contributions of the paper are as follows:1)According to the inherent defects of the easily disturbed of the VLBI technology,the data of celestial navigation is simulated based on the measured data of Chang'e-3(CE-3)and the VLBI single point positioning algorithm.The influence of different star sensor precision on celestial navigation is analyzed.The data are calculated by combining VLBI and celestial navigation,and the results are compared with the results of single solution of celestial navigation and single solution of VLBI.2)A joint positioning model of VLBI combined celestial navigation is proposed by using the conversion relationship between the Selenocentric Cartesian coordinate and the Selenocentric geodetic coordinate.The observation equation is derived and a posteriori estimation method of Helmert method of variance components has been used to determine the weight of two kinds of different positioning systems.3)According to least square method,the positioning value of different time is not connected with each other,and the positioning results are very rough and messy.In this paper,the federated kalman filter is used to calculate the joint system,and the results are compared and analyzed with the least square solution.
Keywords/Search Tags:Lunar Rover, VLBI, Celestial Navigation, Joint Positioning, Federated Kalman Filter
PDF Full Text Request
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