Automatic Satellite’s Streak Detection in Astronomical Images Based on Intelligent Methods

The orbit determination in one sentence is the application of a variety of techniques for estimating the orbits of objects such as the moon, planets and spacecraft. In dynamic astronomy, the orbit determination is the process of determining orbital parameters with observations. Considering the visibility of the satellite motion trace and the fundamental need to determine and modify satellites’ orbital parameters as well as identify special satellites, determining the positional parameters of the satellite is also one of the modern and important applications of vision-based astronomical systems. In the modern vision-based astronomical systems, data collection is done using a charge-coupled device (CCD) array. In this paper, a new method is presented for satellite streak detection through an optical imaging system. This automatic and efficient method, which has the ability of real-time data analysis, is based on the sidereal image using CCDs. The images captured by this method have a large amount of information about stars, galaxy, and satellites’ streaks. In this paper, an automatic method is presented for streak detection. The purpose of this research is to find an optimal method for satellite streak detection and different methods in clustering such as k_means, particle swarm optimization (PSO), genetic algorithm (GA), and Gaussian mixture model (GMM). Finally, some assessment criteria were compared and concluded that GA is an optimal algorithm in satellite streak detection.

Automatic Satellite’s Streak Detection in Astronomical Images Based on Intelligent Methods Keywords:

satellite tracking , satellite streak detection , MSAC , Clustering , swarm intelligence