Session
Technical Session XI: The Technology Frontier-- Advanced Technologies, Subsystems, and components for Small Satellites: Section II
Abstract
This paper presents a study using Genetic Algorithms (GA) to solve the star pattern recognition problem associated with star tracker attitude determination systems. Characteristics of the stars that are visible within the Field of View (FOV) of an imager are defined with regard to relative distances and angles. The proposed GA minimizes the discrepancy between the characteristics of the stars inside the actual FOV and a candidate FOV selected from the star map in order to determine the inertial coordinates of the FOV bore sight. The proposed algorithm has the capability of determining the rotational angle between the spacecraft’s coordinate system and that of a standardized star map. Simulations indicate that the GA approach is highly suited for this type of problem.
Presentation Slides
Star Pattern Recognition for Attitude Determination using Genetic Algorithms
This paper presents a study using Genetic Algorithms (GA) to solve the star pattern recognition problem associated with star tracker attitude determination systems. Characteristics of the stars that are visible within the Field of View (FOV) of an imager are defined with regard to relative distances and angles. The proposed GA minimizes the discrepancy between the characteristics of the stars inside the actual FOV and a candidate FOV selected from the star map in order to determine the inertial coordinates of the FOV bore sight. The proposed algorithm has the capability of determining the rotational angle between the spacecraft’s coordinate system and that of a standardized star map. Simulations indicate that the GA approach is highly suited for this type of problem.
