Star Catalog Generation for Satellite Attitude Navigation Using Density Based Clustering | Science Publications

Journal of Computer Science

Imas Sukaesih Sitanggang¹  Muhammad Arif Saifudin¹  Bib Paruhum Silalahi¹ 

关键词: Star Sensor;    Star Catalog;    Star Identification;    Clustering Method;    DBSCAN;   

DOI  :  10.3844/jcssp.2015.1082.1089

学科分类：计算机科学（综合）

来源: Science Publications

【 摘 要 】

A new method to generate star catalog using density-based clustering is proposed. It identifies regions of a high star density by using Density-Based Spatial Clustering of Application with Noise (DBSCAN) algorithm. Reducing the number stars performed by storing the brightest star in each cluster. The brightest star and all non-clustered members are then stored as a navigation star candidate. Monte Carlo simulation has performed to generate random FOV to check the uniformity of the new catalog. Succeed parameter is if there are at least three stars in the FOV. The simulation results compare between DBSCAN method and Magnitude Filtering Method (MFM) which is the common method to generate star catalog. The result shows that DBSCAN method is better than MFM such for number of star 846 DBSCAN has success 100% while MFM 95%. It concluded that density-based clustering is a promising method to select navigation star for star catalog generation.

【 授权许可】

Unknown