Research On The Autonomous Navigation Method For Planet Landing Based On Distance Measurement

Autonomous navigation technology is one of the key technologies to achieve precise landing of planets.Compared with passive navigation sensors such as optical cameras,LIDAR has advantages such as high accuracy and independence of star light source.Autonomous navigation based on ranging imaging is the research focus of planetary landing detection.Based on the characteristics of planetary landing,this dissertation conducts research on autonomous navigation method based on ranging imaging for the matching of measurement data,navigation filter estimation,optimal measurement configuration and so on.The main contents are as follows:Firstly,the dynamic model and observation model of the planetary landing are established,and the autonomous navigation scheme of the landing is designed.The orbit dynamics model and attitude dynamics model of the lander are established respectively.The characteristics of the LIDAR ranging are analyzed.The navigation sensor models are established.On the basis,the planetary landing navigation scheme based on the ranging imaging is designed.Secondly,according to the matching problem of laser radar 3-D measurement data,the matching method of distance information based on point sets corresponding is studied.Converting the measurement data matching problem to the point set corresponding problem,and by using the iterative closest point algorithm,the corresponding matching of three-dimensional point sets is realized,based on lander position and attitude solving relationship and the point-to-point set closest distance as the matching index,and the relative position and attitude are obtained simultaneously.Then,based on the virtual datum point interpolation,a relative pose solution method for the end of landing datum sparsity problem is studied,and a navigation filter is designed.Considering the sparseness of the baseline data,the adjacent frames recursive registration algorithm and the virtual data interpolating algorithm are studied respectively,and the relative pose state is solved.The extended Kalman filter algorithm is used to design the landing trajectory filter and attitude filter.Finally,an optimal measurement configuration analysis based on plane fitting error is carried out to optimize the LIDAR observation scheme.Taking the three-vector measurement as the object of study,the landing plane normal vector is introduced as the reference variable for error analysis.The landing plane fitting error equation is deduced.Through analyzing the influence of measuring distance error and measuring angle error to the error formula,the influence of variables on landing accuracy is summarized.