VISION-BASED NAVIGATION ALGORITHM FOR PRECISION LANDING
- Paper number
IAC-09.A3.I.9
- Author
Mr. Yang Tian, Harbin Institute of Technology, China
- Coauthor
Mr. Pingyuan Cui, Harbin Institute of Technology, China
- Coauthor
Mr. Cui Hutao, Harbin Institute of Technology, China
- Year
2009
- Abstract
In this paper we propose a visual algorithm for use by a deepspace exploration spacecraft to autonomous estimate the relative position and attitude during the descent phase. This algorithm is composed of the relative motion recovery which provides part motion states estimates based on tracing feature through the monocular image sequence, and landmark matching algorithm which supplies the scale of the relative motion and absolute position of spacecraft. The landmarks discussed here are craters on the surface of celestial body, whose locations are known by reconstructing the celestial body’ 3D model when spacecraft orbits around. To reduce the costs of recovering motion and take good use of previous dates, the recursive estimate algorithm is used in our approach. We describe the formulation model of the navigation camera and the spacecraft kinematics firstly. Based on these models an extended Kalman filter (EKF) is designed to estimate the translation and rotation components between frames. Another reason of choosing EKF is that the filter ensures the estimate result accuracy when the navigation images are under the influence of the noise which is more severe in deepspace environment. The output of the filter is only the spacecraft’s translation vector with a scale and rotation velocity. Landmarks detecting and associating to a database is implemented to obtain the craters’ position in celestial body fixed frame. Locating from the known landmarks has been studied in many ways, but we focus on using the distance between two craters or the major axis to find solution of the scale. Since this distance can be expressed as an angle in camera frame, the spacecraft is located on an spherical surface which contains all the positions that have the same angle. According to the principle, the motion scale can be solved by measuring the angle in tow frames when the initial position is known. This algorithm enable motion estimate when the spacecraft descents and observes less craters. And it is a critical technology for deepspace exploration mission. The results on synthetic image show that the proposed algorithm can provide the estimation of state with satisfactory accuracy.
- Abstract document
- Manuscript document
(absent)