Star Catalog Generation for Satellite Attitude Navigation Using Density Based Clustering

Abstract

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.

Penyelarasan Arah Vektor Gradien Untuk Menentukan Step Size Metode Steepest Descent Pada Fungsi Nonlinear Kuadratik Banyak Variabel

“…Pencarian nilai minimum dan maksimum ini dalam penerapannya dapat dilihat antara lain pada [5,6,[9][10][11][12][13]15…”

Use of Ant Colony Optimization Algorithm for Determining Traveling Salesman Problem Routes

“…Some examples of studies of optimization techniques are modifying of steps in the steepest descent method [1] - [3], computational test of Newton's method variance algorithm on nonlinear optimization problems without constraints [4], comparison of sensitivity analysis on linear optimization using optimal partition and optimal basis [5], elaborating a combination method for solving nonlinear equations [6], overview of Newton's optimization method [7]. Optimization is applied in many aspects of life such as generating star catalogue for satellite attitude navigation using density-based clustering [8], but many of them are applied to transportation and distribution systems [9] - [11].…”

Uniform Star Catalogue using GWKM Clustering for Application in Star Sensors

“…Saifudin et al (2015) proposed a new method for generating a star catalogue on the basis of a clustering algorithm, in which the areas with higher star density are identified by using the Density-Based Spatial Clustering of Application with Noise (DBSCAN) algorithm and then the brightest star of each cluster and all non-cluster members are stored to reduce the size of the catalogue. Finally, in order to examine the uniformity, a Monte Carlo simulation was used to produce a random field of view to observe at least three stars.…”