IMPLEMENTATION AND SIMULATION OF STAR CENTROIDING ALGORITHM BASED ON C++ OF A STAR SENSOR WITH CENTER OF GRAVITY AND WEIGHTED CENTER OF GRAVITY METHOD

This research focuses on one of the components in a satellite or spacecraft, namely the ADCS (attitude determination and control system), especially the star sensor. The star sensor is one of the attitude sensor for a spacecraft that works by utilizing the position of stars visually in a certain...

Full description

Saved in:
Bibliographic Details
Main Author: Carlos Xaverius Pardede, David
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/70956
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Institut Teknologi Bandung
Language: Indonesia
Description
Summary:This research focuses on one of the components in a satellite or spacecraft, namely the ADCS (attitude determination and control system), especially the star sensor. The star sensor is one of the attitude sensor for a spacecraft that works by utilizing the position of stars visually in a certain field of view (FOV), taking into account various influential variables, such as star brightness, camera quality, star catalog, and the algorithm used. The algorithm in question is a star centroiding algorithm, a stage in star pattern recognition that detects star images and calculates the position of each star in the FOV. This study aims to implement two existing star centroiding methods, namely the center of gravity method and the center of gravity weighting method, into a program, using the C++ language. The performance of the applied algorithm will be tested with two characteristics, namely accuracy and processing time through digital simulation. The digital simulation results show that the algorithm that has been applied shows high accuracy for both methods, with an average error of 0.0463% and 0.0467% for the center of gravity and center of gravity weighting methods, respectively, from a number of simulations of 1500. The simulation also shows an average processing time of 19.9 ms and 20.4 ms for both methods, respectively.