Optimization method for star recognition of LAPAN star sensor

LAPAN-A3/IPB satellite carries a star sensor using a star catalog containing selected star data with identity-based clustering methods, namely Density-based Spatial Clustering of Application with Noise (DBSCAN), a visual magnitude-based filtering method and serial search method in the star recognition process. It takes a relatively long time to identify and match star data obtained one by one with the star data in the catalog. Aiming to increase the speed of recognition of stars, in this research an algorithm is optimized, in terms of grouping and recognition of stars in catalog using an optimized hash method. This method allows faster recognition of stars because the data has been arranged with a certain pattern, so it does not require a long time to recognize and match the data obtained. The star catalog used is the star data resulting from optimization using DBSCAN method, which is then reorganized according to a certain range value. Based on the results of simulations and analyzes, the optimization results are able to reduce search time of data in star catalog up to 60% than serial search method.