STUDI KARAKTERISASI DAN PERBANDINGAN ROBUSTNESS PADA BERBAGAI ALGORITMA STAR PATTERN RECOGNITION UNTUK STAR SENSOR MENGGUNAKAN DIGITAL SIMULATION

• Main Author: Setya Ardi, Nugraha
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/33736
• Institution: Institut Teknologi Bandung

The last few years the use of star sensor, which is the most accurate sensor on satellites, began to penetrate into micro satellites and nano satellites, previously used only on high-end satellites. The principle of star sensor is to match the star pattern on the star image captured by the camera with the star pattern on the GSC (Guide Star Catalog). Star sensors have two aspects, namely hardware and software or algorithms. Algorithm on star sensor is also called star pattern recognition algorithm. A good algorithm must have a high level of matching success when there are a lot of disturbances (robust) and fast processing time. There are different types of star pattern recognition algorithms, which have their respective advantages and disadvantages, so it is necessary to characterize and compare the various algorithms. In this final project, the characterization and comparison of robustness in different types of star pattern recognition algorithm are done using digital simulation made in Matlab 2014a. Digital simulation is a simulation performed on software from star image simulation to pattern matching and attitude determination. The simulation results show that the success rate does not always rise with the number of stars used for matching because it depends on how the algorithm works. In addition, the more the number of stars used, the longer processing time, and vice versa. The best algorithm in terms of success rate is an algorithm that uses a combination pattern of all possible triangles, in other words most robust, but has the longest processing time. This long processing time can be overcome by optimizing GSC.