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Characteristics study and robustness comparison of various star pattern recognition algorithm for star sensor using digital simulation
Ardi N.S.a, Poetro R.E.a, Arif Saifudin M.b, Fathurrohim L.a, Courie I.A.a
a Faculty of Mechanical and Aerospace Engineering, Bandung Institute of Technology, Indonesia
b Indonesian National Institute of Aeronautics and Space (LAPAN), Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© Published under licence by IOP Publishing Ltd.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.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Characteristics studies,Digital simulation,Fast processing time,Guide star catalogues,Longest processing time,Processing time,Star pattern recognition,Star sensors[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1088/1755-1315/284/1/012038[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]