🔭 astrophysics

The Space Debris Tracking and Surveillance program of the IAC80 telescope

This paper outlines the adaptation of the IAC80 telescope at the Teide Observatory for automated Space Surveillance and Tracking, highlighting its specialized instrumentation, autonomous operations, and the real-time SATRED data pipeline that enables high-precision astrometric measurements of space debris across Low, Medium, and Geostationary Earth Orbits.

Original authors: Olga Zamora

Published 2026-06-24

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CC BY 4.0

Original authors: Olga Zamora

Original paper licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

Imagine the sky above us is no longer just a quiet, starry canvas, but a busy, chaotic highway filled with thousands of speeding cars (satellites) and loose change (space debris). If we don't keep a close eye on this traffic, collisions could happen, potentially crashing valuable spacecraft or even raining debris down on Earth.

This paper is about a specific "traffic cop" stationed in the Canary Islands: the IAC80 telescope. Originally built to gaze at distant stars, this telescope has been repurposed since 2015 to watch our own neighborhood in space. Here is how it works, explained simply:

1. The Telescope: A Reliable Watchdog

The IAC80 sits on Mount Teide in Tenerife, Spain. It's like a high-quality camera on a sturdy tripod that has been there for decades. The location is perfect because the sky is usually clear and the air is stable, allowing for long, uninterrupted shifts. While it was designed to look at faint stars, its mechanical stability makes it excellent at tracking fast-moving objects like satellites.

2. The Eyes: Two Specialized Cameras

To do its job, the telescope uses two different "eyes" (cameras), each with a special superpower:

CAMELOT2: Think of this as the steady, all-seeing eye. It's a large, sensitive camera that takes detailed photos. It's great for general monitoring and can see a wide patch of sky at once. It's the workhorse that handles most of the routine tracking.
CARONTE: This is the high-speed, high-definition eye. It's a newer, super-fast camera designed to snap pictures incredibly quickly. It's like a sports photographer capturing a sprinter in mid-stride. It's used for getting very sharp, detailed looks at specific objects to understand what they are made of.

3. The Brain: The "Self-Learning" Autopilot

You can't have a human staring through the telescope all night; it would be too slow and tiring. So, the team built a smart software system that acts like an autonomous autopilot.

The Scheduler: This part of the brain knows exactly where every satellite should be at any given second, based on complex math (ephemeris).
The Learner: This is the clever part. If the telescope misses a target by a tiny bit, the software remembers that mistake. Next time, it automatically adjusts the aim to be more accurate. It's like a golfer who keeps adjusting their swing slightly after every shot until they hit the ball perfectly every time.
The Loop: The system picks a target, points the telescope, waits for the perfect moment, snaps a photo, and then immediately moves to the next target without a human needing to touch a button.

4. The Instant Translator: SATRED

Once the camera snaps a photo, the data needs to be understood immediately. Enter SATRED, a real-time data pipeline. Think of SATRED as a super-fast translator that works while the photos are being taken.

Cleaning the Lens: First, it removes any "dust" or static from the image (calibration).
Finding the Needle: It scans the dark sky for long, thin streaks of light. Since satellites move while the camera is open, they don't look like dots; they look like lines or trails.
Measuring: Once it finds a trail, it measures exactly where it is and how bright it is. It uses a clever trick: it looks at the "noise" around the trail to figure out the background sky brightness, then subtracts that to get a clean measurement of the satellite itself.
The Result: Within seconds, the system knows the exact location of the space junk or satellite and sends that data to the European Space Surveillance network.

5. How Well Does It Work?

The paper reports that this system is a huge success.

Volume: On a single clear night, the telescope can track and measure about 1,400 objects.
Precision: It is incredibly accurate, pinpointing locations with a precision better than one arcsecond (which is like seeing a coin from a mile away).
Reliability: It has been running smoothly for years, proving that you can take an old-school astronomy telescope and turn it into a modern, automated space traffic monitor.

The Future

The team isn't stopping there. They plan to upgrade the telescope's "engine" to make it move even faster (up to 1 degree per second) and add new cameras to get even better pictures. The goal is to keep this "traffic cop" working efficiently to keep our orbital highways safe.

In short, the IAC80 telescope has successfully transformed from a stargazer into a space-traffic manager, using smart cameras and self-learning software to keep a constant, automated watch over the growing crowd of objects orbiting our planet.

Technical Summary: The Space Debris Tracking and Surveillance Program of the IAC80 Telescope

Problem Statement
The rapid proliferation of artificial objects in Earth orbit has created significant collision risks for operational spacecraft and ground infrastructure. Consequently, Space Surveillance and Tracking (SST) has become a critical activity for monitoring the orbital environment and characterizing space objects. While optical ground-based telescopes are fundamental for tracking objects in Medium Earth Orbit (MEO) and Geostationary Earth Orbit (GEO), there is a need to adapt existing astronomical facilities into automated, efficient sensors capable of integrating into European SST networks.

Methodology and System Architecture
The paper details the adaptation of the IAC80 telescope, an 82 cm classical Cassegrain instrument located at the Teide Observatory in Tenerife, Spain, for dedicated space debris tracking. Since 2015, the facility has been progressively modified to support autonomous operations across Low Earth Orbit (LEO), MEO, and GEO regimes. The system relies on three core pillars:

Instrumentation:
- CAMELOT2: The primary instrument, featuring a 4k × 4k back-illuminated CCD (E2V CCD231-84) with a pixel scale of 0.326 arcseconds/pixel. It utilizes a C#-based GUI (CCD-Cap) for real-time control of camera parameters, filter selection, and automated observing macros.
- CARONTE: A secondary high-resolution sCMOS camera (Sony IMX461, 102 megapixels) introduced in 2022. It offers a finer pixel scale (0.081 arcseconds/pixel) and low readout noise, controlled via a Python-based GUI for fast imaging and detailed satellite characterization.
Automation and Control:
The system employs a self-learning Pointing Estimator that analyzes historical pointing data to refine telescope accuracy over time. An Ephemeris Selector module plans observations based on predicted satellite positions and visibility constraints. The operational workflow involves selecting an ephemeris, slewing the telescope, and executing exposures. Crucially, the system incorporates a feedback loop: if pointing errors from previous exposures are significant, the system triggers an updated pointing command; if errors are small, it proceeds directly to the next exposure to optimize efficiency.
Real-Time Data Reduction (SATRED):
A custom pipeline, SATRED (SATellite REDuction), processes data on-the-fly. Its workflow includes:
- Calibration: Automatic bias subtraction and flat-fielding using master frames.
- Trail Detection: A robust algorithm that estimates background levels using median statistics and standard deviation. It applies a threshold ( $N\sigma$ ) to select candidate pixels, followed by Gaussian smoothing (7×7 kernel) to merge fragmented trail segments.
- Geometric Characterization: Contours are extracted, and convex hulls are analyzed. Candidates are filtered based on minimum area and an elongation ratio ( $R_i = L_i/S_i$ ) to distinguish linear satellite trails from point sources or noise.
- Photometry and Astrometry: For valid trails, a rectangular aperture aligned with the trail orientation integrates flux, while a surrounding sky region (separated by a configurable gap) estimates the local background. The pipeline outputs centroid coordinates, area, length, and integrated flux, performing astrometric measurements to achieve sub-arcsecond precision.

Key Results
The IAC80 system demonstrates high operational reliability and data acquisition rates:

Throughput: Under typical conditions, the system acquires approximately 1,400 measurements per night for MEO and GEO targets. Fewer measurements are obtained for LEO targets due to their higher apparent motion.
Precision: The system routinely delivers astrometric precision better than one arcsecond across different orbital regimes.
Efficiency: Detection efficiency is reported to be between 80% and 90% under nominal observing conditions.
Consistency: The system has maintained stable performance over multiple years, successfully integrating into the European SST network.

Significance and Claims
The paper asserts that the IAC80 program successfully demonstrates the efficacy of repurposing classical astronomical facilities for operational SST applications. By integrating dedicated instrumentation, self-learning automation tools, and a real-time data reduction pipeline, the telescope has evolved from a research instrument into a reliable contributor to European space surveillance efforts. The work highlights that such adaptations can provide the high-volume, accurate tracking data necessary to protect space assets, specifically validating the role of the IAC80 as a robust sensor for MEO and GEO monitoring.

Future Directions
The authors outline planned upgrades to further enhance the system's capabilities, including:

Improvements in photometric calibration and multi-filter satellite characterization.
Optimization of automation and scheduling algorithms.
Hardware upgrades comprising a modern control system, a wide-field camera, and new engines to increase the angular tracking velocity from 0.5 degrees/second to 1 degree/second.