How Satellite Tracking Works

More than 16,000 active satellites currently orbit the Earth, and the number is growing rapidly. SpaceX's Starlink constellation alone accounts for over 10,000 of them — roughly two-thirds of all active spacecraft — and with Amazon's Project Kuiper, China's Guowang constellation, and dozens of other operators deploying spacecraft, the total population of active satellites could exceed 50,000 within the next decade.

Tracking all of these objects -- along with spent rocket stages, defunct satellites, and fragments from collisions and explosions -- is one of the most complex operational challenges in the space domain. Satellite tracking, formally known as space situational awareness (SSA) or space domain awareness (SDA), involves detecting, cataloging, and predicting the positions of objects in Earth orbit to prevent collisions, ensure mission success, and maintain the long-term sustainability of the space environment.

This guide explains the fundamental physics, technology, data formats, and operational processes that make satellite tracking possible. Whether you are a satellite operator, a student of orbital mechanics, an investor evaluating SSA companies, or simply curious about how we keep track of objects moving at 7.5 kilometers per second, this is a comprehensive starting point.

Satellite tracking is grounded in the physics of orbital mechanics, which describes the motion of objects under the influence of gravity. The foundational work was established by Johannes Kepler (whose three laws of planetary motion describe the shape, speed, and period of orbits) and Isaac Newton (whose law of universal gravitation provides the mathematical framework for calculating trajectories).

In idealized two-body mechanics (one massive body, one negligible mass), an orbit is fully described by six parameters known as Keplerian orbital elements:

In practice, real orbits are not perfectly Keplerian. They are perturbed by Earth's non-spherical gravity field (particularly the J2 oblateness term), atmospheric drag (significant below ~800 km altitude), solar radiation pressure, lunar and solar gravitational influences, and relativistic effects. Accurate orbit determination must account for all of these perturbations, which is why orbit prediction is computationally intensive and why tracking data must be updated regularly.

Different types of orbits serve different purposes, and each presents distinct tracking challenges.

Low Earth Orbit (LEO): 200-2,000 km

LEO is the most populated orbital regime, home to the International Space Station (~415 km), Starlink (~550 km), Planet Labs satellites (~475 km), and most Earth observation and scientific satellites. Objects in LEO complete an orbit in approximately 90 to 130 minutes and travel at roughly 7.5 km/s. LEO satellites are subject to significant atmospheric drag, especially below 500 km, which causes orbital decay and makes long-term orbit prediction more challenging. Radar is the primary tracking method for LEO objects.

Medium Earth Orbit (MEO): 2,000-35,786 km

MEO is used primarily for navigation satellites (GPS at ~20,200 km, Galileo at ~23,222 km, GLONASS at ~19,100 km) and some communication constellations (Eutelsat OneWeb at ~1,200 km, technically upper LEO). MEO satellites orbit more slowly than LEO objects (periods of 2-24 hours) and experience less atmospheric drag, making their orbits more predictable. Tracking at MEO altitudes typically uses a combination of radar and optical methods.

Geostationary Orbit (GEO): ~35,786 km

GEO is a circular orbit at approximately 35,786 km altitude where the orbital period matches Earth's rotation, causing the satellite to appear stationary over a fixed point on the equator. GEO is used for communications satellites (SES, Intelsat, Viasat), weather satellites (GOES, Meteosat), and some military early warning systems. GEO satellites are typically tracked using optical telescopes, as the distance makes radar tracking more challenging. The GEO belt is a finite resource, with orbital slots allocated by the International Telecommunication Union (ITU).

Highly Elliptical Orbits (HEO)

HEO orbits, such as Molniya orbits (used by Russia for high-latitude communications) and Tundra orbits, have high eccentricity, spending most of their orbital period at high altitudes over specific regions. These orbits present unique tracking challenges due to the wide range of altitudes and velocities involved.

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Radar Tracking

Radar is the workhorse of satellite tracking for objects in low Earth orbit. Tracking radars emit radio pulses and measure the time, direction, and Doppler shift of reflected signals to determine an object's range, azimuth, elevation, and radial velocity. The U.S. Space Surveillance Network (SSN) operates several powerful radar systems, including the AN/FPS-85 phased array radar at Eglin Air Force Base (Florida), the Space Fence on Kwajalein Atoll (Marshall Islands), and several other dedicated tracking radars.

The Space Fence, which became operational in 2020, is a ground-based S-band radar system that represents a major upgrade in U.S. tracking capability. Operating in the Kwajalein Atoll, it can detect and track objects as small as 10 centimeters in LEO, significantly smaller than previous systems. The Space Fence has increased the U.S. catalog by thousands of newly tracked objects.

Optical Tracking

Optical tracking uses telescopes equipped with CCD or CMOS sensors to observe satellites by the sunlight they reflect. Optical methods are particularly effective for tracking objects in GEO and MEO, where radar range limitations make radio-based tracking less practical. Optical observations can provide highly accurate angular position measurements but depend on favorable lighting conditions -- the satellite must be illuminated by the sun while the observer is in darkness (typically during twilight hours for LEO observations).

The U.S. operates the Ground-Based Electro-Optical Deep Space Surveillance (GEODSS) system at sites in New Mexico, Hawaii, and Diego Garcia, specifically designed to track objects in deep space (GEO and beyond). Commercial providers like ExoAnalytic Solutions operate global networks of commercial telescopes for GEO tracking and characterization.

Passive RF Tracking

Some tracking systems detect the radio frequency (RF) emissions from active satellites -- their telemetry, beacon signals, or communication transmissions. This passive approach can identify and locate satellites without emitting any signals. Companies like HawkEye 360 operate satellite constellations that geolocate RF emitters from space, which can include satellite signals.

Laser Ranging (SLR)

Satellite Laser Ranging (SLR) provides the highest precision tracking measurements available, achieving millimeter-level accuracy by bouncing short laser pulses off retroreflectors mounted on certain satellites. The International Laser Ranging Service (ILRS) coordinates a global network of approximately 40 SLR stations. While SLR is too resource-intensive for routine tracking of the full catalog, it provides critical data for geodesy, precise orbit determination of reference satellites, and calibration of other tracking systems.

The U.S. Space Surveillance Network (SSN) is the world's most comprehensive satellite tracking system. Operated by the U.S. Space Force's 18th Space Defense Squadron at Vandenberg Space Force Base, the SSN consists of over 30 radar and optical sensor sites distributed around the globe. The SSN tracks approximately 48,000 objects larger than 10 cm in LEO and 1 meter in GEO, performing over 400,000 observations per day.

The SSN's catalog data is published through Space-Track.org, operated by the 18th Space Defense Squadron. Registered users can access Two-Line Element sets (TLEs), conjunction data messages (CDMs), and other orbital data. This publicly shared data forms the backbone of most civilian and commercial satellite tracking worldwide.

Other Government Networks

Russia operates its own space surveillance system, the Space Surveillance System (SSS), though it shares limited data publicly. The European Space Surveillance and Tracking (EU SST) program, established in 2014 and expanded through the EU Space Programme, coordinates sensor assets across EU member states including radar systems in Spain and France and optical telescopes in the Canary Islands and elsewhere. Japan's JAXA operates the Kamisaibara Space Guard Center with radar and optical sensors, and Australia contributes tracking capabilities through facilities at Pine Gap and a growing network of optical sensors.

The Two-Line Element set (TLE) is the standard data format for distributing satellite orbital parameters. Developed by NORAD in the 1960s and still in widespread use, a TLE encodes the essential orbital elements and related parameters in two lines of 69 characters each, preceded by a title line.

ISS (ZARYA)
1 25544U 98067A   26038.51234567  .00016717  00000-0  10270-3 0  9993
2 25544  51.6416 247.4627 0006703 130.5360 229.6100 15.50000000123456

Each field in a TLE carries specific information. Line 1 includes the satellite catalog number (25544 for the ISS), the international designator (98067A, meaning the 67th launch of 1998, object A), the epoch (the date and time to which the orbital elements are referenced), the first and second derivatives of mean motion (related to drag), and the BSTAR drag coefficient. Line 2 contains the orbital elements themselves: inclination, RAAN, eccentricity, argument of perigee, mean anomaly, and mean motion (revolutions per day).

TLEs are designed to be used with the SGP4/SDP4 propagator, a mathematical model that predicts a satellite's future position based on its TLE. The SGP4 model accounts for Earth's oblateness (J2 perturbation), atmospheric drag, and solar/lunar effects in a simplified but computationally efficient manner. Using a TLE with a different propagator will produce incorrect results, as the TLE elements are not true Keplerian elements but rather "mean" elements that absorb certain perturbation effects.

TLE accuracy degrades over time as perturbations cause the actual orbit to diverge from the prediction. For LEO objects, a TLE is typically accurate to within a few kilometers for the first day after epoch, degrading to tens of kilometers within a week. GEO TLEs tend to maintain better accuracy over longer periods due to the absence of atmospheric drag. TLEs are updated regularly -- typically every few days for most cataloged objects, and more frequently for objects of high interest.

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Orbit propagation is the process of predicting a satellite's future position based on its current orbital state and a mathematical model of the forces acting on it. The choice of propagator depends on the accuracy required and the computational resources available.

SGP4/SDP4 (Simplified General Perturbations)

SGP4 (for near-Earth objects, period < 225 minutes) and SDP4 (for deep-space objects) are the standard propagators used with TLE data. Developed by the U.S. Air Force in the 1960s and refined through the 1980s, SGP4 remains the most widely used propagator in the world due to its computational efficiency and the ubiquity of TLE data. However, its accuracy is limited -- typically to a few kilometers after one day of propagation for LEO objects.

High-Fidelity Numerical Propagators

For applications requiring greater accuracy -- such as mission planning, conjunction assessment, and precise orbit determination -- high-fidelity numerical propagators are used. These integrate the equations of motion step by step, incorporating detailed force models including high-order gravity field harmonics (up to 70x70 or higher), atmospheric density models (NRLMSISE-00, JB2008), solar radiation pressure with shadow modeling, third-body perturbations from the Moon and planets, and solid Earth and ocean tides. Software packages like AGI's STK, GMAT (NASA's open-source General Mission Analysis Tool), and Orekit (open-source Java library) provide high-fidelity propagation capabilities.

Atmospheric Drag: The Biggest Uncertainty

For satellites in LEO below approximately 800 km, atmospheric drag is the dominant source of orbit prediction uncertainty. The Earth's upper atmosphere (thermosphere) is highly variable, with density changing by factors of ten or more depending on solar activity, geomagnetic storms, and time of day. During major solar storms, atmospheric density can increase dramatically, causing unexpected orbital decay. This is precisely what happened with the loss of 38 Starlink satellites in February 2022, when a geomagnetic storm increased atmospheric drag to levels that prevented the newly launched satellites from reaching their operational orbit.

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Conjunction assessment (CA) is the process of identifying close approaches between objects in orbit and evaluating the risk of collision. With over 48,000 tracked objects and billions of potential pairings, this is a computationally intensive screening process performed continuously by the 18th Space Defense Squadron.

When two objects are predicted to pass within a defined screening volume (typically a few kilometers), a Conjunction Data Message (CDM) is generated and shared with the affected satellite operator. The CDM contains the predicted time of closest approach (TCA), the miss distance, the relative velocity, and the covariance matrices (uncertainty ellipsoids) for both objects. From this data, a probability of collision (Pc) can be calculated.

When the probability of collision exceeds a defined threshold -- typically 1 in 10,000 (10^-4) for high-value assets like the ISS -- the satellite operator may perform a collision avoidance maneuver (CAM), adjusting the satellite's orbit to increase the miss distance. NASA's Conjunction Assessment team at the Goddard Space Flight Center supports conjunction assessment for NASA missions, including the ISS, which performs several collision avoidance maneuvers per year.

SpaceX has implemented an autonomous collision avoidance system for Starlink, which processes CDMs and executes avoidance maneuvers without human intervention. The company reports performing thousands of maneuvers annually. As the number of satellites grows, the frequency and complexity of conjunction events increases non-linearly, making automated collision avoidance systems increasingly essential.

While government tracking networks provide the foundation, a growing commercial SSA industry has emerged to fill capability gaps and provide differentiated services to satellite operators, insurers, and government customers.

LeoLabs

LeoLabs operates a global network of phased-array radars optimized for tracking objects in LEO. With radar sites in New Zealand, Texas, Costa Rica, Australia, and the Azores, LeoLabs provides commercial tracking services including a maintained LEO catalog, conjunction screening, and analytics. The company claims to track objects as small as 2 centimeters in certain orbital regimes and provides position accuracy of approximately 10-20 meters.

ExoAnalytic Solutions

ExoAnalytic operates the world's largest commercial network of optical telescopes, with over 300 sensors at sites globally. The company specializes in tracking objects in GEO and cislunar space, providing characterization data (identifying what an object is, not just where it is) and anomaly detection for satellite operators and government customers.

Other Commercial Providers

Numerica Corporation provides a commercial space catalog and collision avoidance services using a combination of owned and partner telescopes. Privateer, co-founded by Apple co-founder Steve Wozniak, is building a space mapping and data platform. COMSPOC (Commercial Space Operations Center) provides independent conjunction screening and space safety services. Slingshot Aerospace offers a space situational awareness platform used by the U.S. Space Force.

Mega-Constellation Growth

The sheer number of satellites being deployed presents an unprecedented tracking challenge. The U.S. catalog has grown from approximately 20,000 objects in 2019 to over 48,000 in 2026, driven largely by Starlink deployments. With Kuiper, Guowang, and other mega-constellations in deployment or planning, the catalog could exceed 100,000 objects within the next decade. Each new object increases the number of potential conjunctions quadratically, straining existing screening capabilities.

Small Debris

Current ground-based tracking systems can reliably detect objects down to approximately 10 cm in LEO and 1 meter in GEO. However, NASA models estimate there are over 100 million pieces of debris larger than 1 mm in orbit, and approximately 500,000 pieces between 1 cm and 10 cm -- large enough to cause catastrophic damage but too small to be tracked and avoided. This "lethal non-trackable" population represents the most dangerous threat to operational spacecraft.

Cislunar and Deep Space Tracking

As activity extends beyond Earth orbit -- to cislunar space (between Earth and the Moon), lunar orbit, and beyond -- existing tracking infrastructure is inadequate. The SSN is optimized for Earth-orbital tracking and has limited capability to monitor objects in cislunar space. New sensor architectures, including space-based telescopes and deep-space radar, will be needed to maintain situational awareness as human and robotic activity in the cislunar domain increases.

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The rapid growth in orbital populations has prompted efforts to establish formal space traffic management (STM) frameworks -- analogous to air traffic management for aviation. In the United States, Space Policy Directive-3 (SPD-3), issued in 2018, directed the transition of civilian space traffic management responsibilities from the Department of Defense to the Department of Commerce. This transition has been slow, with the Office of Space Commerce (OSC) developing the Traffic Coordination System for Space (TraCSS) to provide basic conjunction screening and notification services to satellite operators.

Internationally, the United Nations Committee on the Peaceful Uses of Outer Space (COPUOS) has published long-term sustainability guidelines that encourage space debris mitigation and best practices for SSA data sharing. However, there is no binding international treaty governing space traffic management, and coordination between spacefaring nations remains largely voluntary and ad hoc.

The space insurance industry is increasingly factoring collision risk and space sustainability into underwriting decisions. Satellite operators that can demonstrate robust collision avoidance capabilities and compliance with debris mitigation guidelines may benefit from favorable insurance terms.

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A range of tools and platforms are available for satellite tracking, from free public resources to sophisticated commercial systems.

For developers and researchers, several open-source libraries provide satellite tracking capabilities. Orekit (Java) is a comprehensive space dynamics library used by ESA and commercial operators. Skyfield (Python) provides high-accuracy astronomical calculations including satellite position prediction. satellite.js is a JavaScript implementation of the SGP4 propagator used in web-based tracking applications.

SpaceNexus provides an integrated satellite tracking and space operations platform that brings together orbital data, constellation monitoring, ground station mapping, and space environment awareness in a single interface.