Resident space object detection method based on the connection between Fourier spectrum of the video data difference frame and the linear velocity projection

TL;DR

This paper introduces a novel RSO detection method using Fourier spectrum analysis of video difference frames linked to linear velocity projections, enabling detection and motion analysis of space objects.

Contribution

The paper presents a new detection approach that correlates Fourier spectrum shape with velocity projections, improving identification of space objects in video data.

Findings

Successfully detected satellites in real video data

Established correlation between Fourier spectrum and inclination angles

Enabled motion parameter analysis of space objects

Abstract

A method for resident space object (RSO) detection in video stream processing using a set of matched filters has been proposed. Matched filters are constructed based on the connection between the Fourier spectrum shape of the difference frame and the magnitude of the linear velocity projection onto the observation plane. Experimental data were obtained using the mobile optical surveillance system for low-orbit space objects. The detection problem in testing mode was solved for raw video data with intensity signals from three different satellites: KORONAS-FOTON, CUSAT 2/FALCON 9, GENESIS 1. Difference frames of video data with the AQUA satellite pass to construct matched filters were used. The satellites were automatically detected at points where the difference in the value of their linear velocity projection and the reference satellite was close in value. It has been established that the difference in the inclination angle between the detected satellite intensity signal Fourier image and the reference satellite mask corresponds to the difference in the inclinations of these objects. The proposed method allows not only to detect but also to study the motion parameters of both artificial and natural space objects, such as satellites, debris and asteroids.