Autonomous Satellite Detection and Tracking using Optical Flow

Abstract

In this paper, an autonomous method of satellite detection and tracking in images is implemented using optical flow. Optical flow is used to estimate the image velocities of detected objects in a series of space images. Given that most objects in an image will be stars, the overall image velocity from star motion is used to estimate the image frame-to-frame motion. Objects seen to be moving with velocity profiles distinct from the overall image velocity are then classified as potential resident space objects. The detection algorithm is exercised using both simulated star images and ground-based imagery of satellites. Finally, this algorithm will be tested and compared using a commercial and an open-source software approach to provide the reader two different options based on their need.

Quasi real-time autonomous satellite detection and orbit estimation

“…19 Other common methods for tracking objects make use of optical flow to detect the motion. 20 The LQE framework will be adapted from tracking object centroids in an image to tracking inertial angular positions of an RSO as it transits the night sky.…”