# Automatic Data Reduction of Image Sequences Acquired in Object Tracking Mode for Detection and Position Measurement of Faint Orbital Objects

## TL;DR

A new automatic method processes telescope images to accurately track faint orbital objects using lightweight tools and real-time tracking.

## Contribution

A novel automatic processing pipeline for precise object tracking images, enabling accurate position measurements of faint orbital objects.

## Key findings

- The method uses filtering and weighted stacking to improve astrometric calibration and signal-to-noise ratio.
- Tests on CLUSTER II satellites showed accurate measurements up to 1300 km from the observer.
- The approach is effective for time-critical campaigns like satellite reentry events.

## Abstract

What are the main findings?
A method for complete automatic processing of images acquired in precise object tracking mode, based on lightweight image operations and freely available calibration tools.Accurate measurement of the position of faint orbital objects.

A method for complete automatic processing of images acquired in precise object tracking mode, based on lightweight image operations and freely available calibration tools.

Accurate measurement of the position of faint orbital objects.

What are the implications of the main findings?
Fast reduction in image sequences using low processing power can generate result tdm files at the observer site immediately after the observation is completed.Helpful for surveying high altitude or high eccentricity objects, especially on time critical campaigns such as reentry events.

Fast reduction in image sequences using low processing power can generate result tdm files at the observer site immediately after the observation is completed.

Helpful for surveying high altitude or high eccentricity objects, especially on time critical campaigns such as reentry events.

Precise object tracking of space objects is an image acquisition method that uses the mount of the telescope to orient the instrument in real time towards the target to be tracked, compensating for the target’s motion. Using this method, the object of interest will appear as a circular or point-like shape in the acquired image, while the background stars will appear as streaks. Using precise object tracking, the light from a faint object accumulates in the same region of the image, increasing the chance of observation, but longer exposures also increase the length of the background star streaks and makes the astrometric calibration difficult. This paper presents a method for the automatic processing of image sequences acquired in precise object tracking mode. Our proposed method includes a filtering mechanism that will ensure local maxima in the center of star streaks in order to allow for a publicly available astrometric calibration software to work even if the stars are not point-like, a weighted stacking mechanism to increase the signal-to-noise ratio for faint targets while excluding the stars, an automatic object detection and astrometric reduction mechanism and a constraint-based filtering of outliers for the final generation of the tracklet. The method was tested on multiple observation sessions for surveying the CLUSTER II highly eccentric orbit satellites, including the CLUSTER II FM5 satellite (Rumba) on its final passes before reentry, and the accuracy of the measurements was estimated based on ground truth from ESA’s reentry team. The method was also tested on lower orbit objects and found to be accurate for objects with ranges of more than 1300 km from the observer.