Open AccessCharacteristics study and robustness comparison of various star pattern recognition algorithm for star sensor using digital simulation
Author(s) -
N S Ardi,
Ridanto Eko Poetro,
Muhammad Arif Saifudin,
Luqman Fathurrohim,
Ilham Akbar Courie
Publication year - 2019
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/284/1/012038
Subject(s) - algorithm , robustness (evolution) , computer science , star (game theory) , stars , a* search algorithm , pattern matching , artificial intelligence , computer vision , mathematics , mathematical analysis , biochemistry , chemistry , gene
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. Hence we need to develop star sensor according to the specific needs of microsatellite and nano satellites. One of star sensor’s aspect is star pattern recognition algorithm. A good star pattern recognition 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 paper, the characterization and comparison of robustness in different types of star pattern recognition algorithm are done using digital simulation. 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 are 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 (Guide Star Catalogue). From the results the multitriangles 2 algorithm has the best success rate compared to the other algorithms, with success rate for 5, 6, and 7 stars configuration are 97.8%, 98.7%, and 99.8% respectively.