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<p align="justify"> The last few years the use of star sensor, which is the most accurate sensor <br /> <br /> on satellites, began to penetrate into micro satellites and nano satellites, previously <br /> <br /> used only on high-end satellites. The principle...

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Main Author: SETYA ARDI (nim : 13614063), NUGRAHA
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/29749
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Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:29749
spelling id-itb.:297492018-06-29T14:37:29Z#TITLE_ALTERNATIVE# SETYA ARDI (nim : 13614063), NUGRAHA Indonesia Final Project INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/29749 <p align="justify"> The last few years the use of star sensor, which is the most accurate sensor <br /> <br /> on satellites, began to penetrate into micro satellites and nano satellites, previously <br /> <br /> used only on high-end satellites. The principle of star sensor is to match the star <br /> <br /> pattern on the star image captured by the camera with the star pattern on the GSC <br /> <br /> (Guide Star Catalog). Star sensors have two aspects, namely hardware and software <br /> <br /> or algorithms. Algorithm on star sensor is also called star pattern recognition <br /> <br /> algorithm. A good algorithm must have a high level of matching success when there <br /> <br /> are a lot of disturbances (robust) and fast processing time. There are different types <br /> <br /> of star pattern recognition algorithms, which have their respective advantages and <br /> <br /> disadvantages, so it is necessary to characterize and compare the various <br /> <br /> algorithms. <br /> <br /> In this final project, the characterization and comparison of robustness in <br /> <br /> different types of star pattern recognition algorithm are done using digital <br /> <br /> simulation made in Matlab 2014a. Digital simulation is a simulation performed on <br /> <br /> software from star photo simulation to pattern matching and attitude determination. <br /> <br /> The simulation results show that the success rate does not always rise with <br /> <br /> the number of stars used for matching because it depends on how the algorithm <br /> <br /> works. In addition, the more the number of stars used, the longer processing time, <br /> <br /> and vice versa. The best algorithm in terms of success rate is an algorithm that uses <br /> <br /> a combination pattern of all possible triangles, in other words most robust, but has <br /> <br /> the longest processing time. This long processing time can be overcome by <br /> <br /> optimizing GSC. <p align="justify"> text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
description <p align="justify"> The last few years the use of star sensor, which is the most accurate sensor <br /> <br /> on satellites, began to penetrate into micro satellites and nano satellites, previously <br /> <br /> used only on high-end satellites. The principle of star sensor is to match the star <br /> <br /> pattern on the star image captured by the camera with the star pattern on the GSC <br /> <br /> (Guide Star Catalog). Star sensors have two aspects, namely hardware and software <br /> <br /> or algorithms. Algorithm on star sensor is also called star pattern recognition <br /> <br /> algorithm. A good algorithm must have a high level of matching success when there <br /> <br /> are a lot of disturbances (robust) and fast processing time. There are different types <br /> <br /> of star pattern recognition algorithms, which have their respective advantages and <br /> <br /> disadvantages, so it is necessary to characterize and compare the various <br /> <br /> algorithms. <br /> <br /> In this final project, the characterization and comparison of robustness in <br /> <br /> different types of star pattern recognition algorithm are done using digital <br /> <br /> simulation made in Matlab 2014a. Digital simulation is a simulation performed on <br /> <br /> software from star photo simulation to pattern matching and attitude determination. <br /> <br /> The simulation results show that the success rate does not always rise with <br /> <br /> the number of stars used for matching because it depends on how the algorithm <br /> <br /> works. In addition, the more the number of stars used, the longer processing time, <br /> <br /> and vice versa. The best algorithm in terms of success rate is an algorithm that uses <br /> <br /> a combination pattern of all possible triangles, in other words most robust, but has <br /> <br /> the longest processing time. This long processing time can be overcome by <br /> <br /> optimizing GSC. <p align="justify">
format Final Project
author SETYA ARDI (nim : 13614063), NUGRAHA
spellingShingle SETYA ARDI (nim : 13614063), NUGRAHA
#TITLE_ALTERNATIVE#
author_facet SETYA ARDI (nim : 13614063), NUGRAHA
author_sort SETYA ARDI (nim : 13614063), NUGRAHA
title #TITLE_ALTERNATIVE#
title_short #TITLE_ALTERNATIVE#
title_full #TITLE_ALTERNATIVE#
title_fullStr #TITLE_ALTERNATIVE#
title_full_unstemmed #TITLE_ALTERNATIVE#
title_sort #title_alternative#
url https://digilib.itb.ac.id/gdl/view/29749
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