The steep increase in satellite launches and the certainty of many more to come are a boon for the industry, but also a major concern for those involved in preserving the sustainability of the space environment. Over the next five years, in low Earth orbit (LEO) alone, as many as 70,000 satellites are forecast to be launched, according to Goldman Sachs, with geostationary orbit (GEO) satellites still expected to remain a significant segment of the satellite market. This aggressive deployment of satellites, particularly in LEO, and continued deployment in GEO, poses a significant challenge for operators who must ensure the safety of flight for their fleets and constellations.

Space situational awareness (SSA) is more critical than ever as we attempt to prevent collisions. We must have accurate knowledge of space objects to enable effective space traffic management, to protect critical infrastructure, promote orbital sustainability and to support operational planning.

This is also coupled with the threat of space debris that litters our orbits and that we are struggling to contain. According to the European Space Agency Space Environment Report, published in 2025, within certain heavily populated altitude bands, the density of active objects is now in the same order of magnitude as that of space debris. This gives a clear indication of the challenge that we are dealing with and the requirement for effective SSA and space traffic management (STM).

THE STATE OF SSA

Traditionally, SSA was provided by large national defense organizations that satellite operators relied upon to maintain a catalog of space objects. Fast forward to today, and the sector has opened up to the commercial industry. Over the last decade, there has been a proliferation of private companies that offer SSA and STM services to inform the industry about the characterization, location and direction of space assets and debris, as well as the probability of close conjunctions and collision avoidance.

SSA AND STM: THE DIFFERENCE

There are notable differences between SSA and STM, and it might be useful to first establish them. SSA is the knowledge of where satellites and items of debris are in the space environment, what they are and their characteristics, as well as their trajectory and velocity. STM is the actual management of space traffic to ensure safety and avoid collisions, so it is that additional layer of knowledge that sits on top of SSA. Both are essential for space sustainability, but how do we get that information?

To give an accurate picture of what is going on in the space environment relies upon complex networks of optical sensors and radar systems. These can be ground- or space-based, and they provide essential data on the movement of objects, from very small pieces of space debris to active satellites.

Although data is provided by satellite owner/operators and pooled for SSA platforms such as the Space Data Association’s (SDA’s) Space Safety Portal, this can often be limited, and therefore additional data is required to fill in gaps and to provide a more accurate picture of what is happening in the space environment at any given time. The use of radar and sensor technology helps fill those gaps and give us a better understanding of the location and nature of objects in space.

CRITICAL INFRASTRUCTURE: RADAR AND SENSORS

Radar and sensor systems are essential for effective SSA. They are used to detect, track and characterize resident space objects, including active satellites, defunct spacecraft and debris. In simple terms, they allow us to measure the positions of objects orbiting the Earth at a given time.

Ground-based and space-based sensors provide measurements such as range, range-rate, angles and signal characteristics. These measurements are the basis for orbit determination and the conjunction assessment process. Once an orbit is determined, it becomes possible to predict where objects are now and where they are expected to be in the coming days.

Sensor data is a fundamental input to maintaining an accurate and up-to-date orbital catalog, which is essential for collision risk monitoring and effective coordination between operators.

RADAR: TRACKING IN LEO

There are several types of ground-based radar that are widely used to track LEO satellites. Radar is considered highly accurate and can handle the frequent revisits of LEO satellites.

Phased array radar (PAR) technology is gaining popularity as it advances and becomes more affordable. With no moving parts and the ability to scan, steer and focus, it is a highly reliable and rapid technology that requires minimal maintenance. Use of emerging techniques such as phase-only beamforming is resulting in higher power efficiency and simpler design. The antenna’s ability to instantaneously steer beams means it can simultaneously track multiple small objects in LEO, such as satellites and debris. The ability to shape its beam also means it can be adjusted to focus on specific areas of interest or zoom out to cover larger areas, including the orbital arc. Emerging technology, such as digital beamforming, allows PAR to detect very small objects, which is extremely useful given the amount of debris under 10 cm that is not currently tracked.

Bi-static radar, where the transmit and receive components are separated, so that the returned waves can be detected instead of deflected, is used to detect, track and image space objects and enables the detection of smaller, faint objects in orbit. The bi-static configuration, combined with high-power transmitters, allows enhanced detection. This can also be achieved using inverse synthetic aperture radar (ISAR), enabling better target recognition.

In a monostatic radar system, the transmitter and receiver are located in the same place. Though this radar system is highly effective at tracking and determining the orbits of objects under all environmental conditions, whether dark or illuminated by the sun, it can be limited by signal loss at very long distances, which can affect its ability to track in GEO.

ISAR is considered highly effective for monitoring space debris and objects too small to be cataloged. It uses the target’s motion to obtain a high-resolution image of it. The detail it can show means that the status of orbiting satellites can be analyzed in real time, so problems with malfunctioning satellites, for example, can be picked up in advance. The range resolution of ISAR is dependent on bandwidth, so the higher the bandwidth, the higher the resolution. ISAR is an area of radar that is undergoing advancements, progressing from 2D to 3D imaging and enhancing capabilities with AI.

OPTICAL SENSORS: TRACKING IN GEO

For satellites in GEO, optical sensors are more widely used as radar’s effectiveness is more limited over longer distances. Optical telescopes, which are passive sensors, are particularly important for GEO and higher orbits. These telescopes gather electromagnetic radiation to form an image. Some telescopes use lenses (refracting), others use mirrors (reflecting) and some combine both (catadioptric). Optical telescopes depend very much on their field of view and aperture, which determine how much of the sky can be seen.

Though highly effective, telescopes must be located far from civilization as they are negated by light pollution and weather. Therefore, ideal locations for telescopes are in remote regions with predictable weather, low light pollution and little cloud cover.

The use of adaptive optics (AO) as a concept for optical sensors has been around for many decades, but this field is constantly advancing to give a much clearer image of objects in orbit. The first component of AO is a wavefront sensor, a fast digital camera that measures atmospheric distortion in real time, hundreds or thousands of times per second, due to rapid changes there. The wavefront requires a bright light reference source above the atmosphere. This is often provided by a laser, called a laser guide star. The third is a deformable mirror, which is made of a reflective membrane that is manipulated by a series of mechanisms on which it sits. These mechanisms correct the mirror, compensating for light distortions. In practice, whether the sensors are radar or optical, they are globally distributed to maximize temporal coverage and provide better geometric diversity.

SPACE-BASED SENSORS

Increasingly, space-based sensors are mounted on LEO satellites. They can be either optical or RF-based and are increasingly being used to complement ground systems. By placing the sensors on board a satellite, they eliminate atmospheric interference and make the tracking of small debris easier. Due to frequent satellite revisits, these sensors can also observe the object of interest more regularly, providing a better understanding of its behavior and enabling a more consistent view of the environment. These sensors improve overall coverage and reduce dependencies on geography, weather and local infrastructure.

TRACKING SMALL SPACE DEBRIS

Tracking very small debris remains challenging, particularly for objects smaller than a few centimeters. That said, advances in high-power radar systems, signal processing techniques, passive RF sensing and sensor networking are steadily improving detection and characterization capabilities. While not all small debris can be individually tracked, improved statistical characterization and modeling are helping operators better understand the associated risk and factor it into operational decision-making.

HOW MUCH SENSOR DATA DO WE NEED?

There is no single threshold that defines a “good” level of SSA. The required amount of data depends on the orbital regime, the object’s size and the mission’s criticality. In practice, measurement quality, revisit rate and sensor diversity tend to be more important than raw data volume alone. Data fusion from multiple independent sensors significantly improves accuracy, robustness and confidence in conjunction assessments.

One of the main challenges is making efficient and reliable use of all the available information while validating the accuracy and consistency of different data sources. Organizations such as the SDA help satellite operators by organizing, prioritizing and operationally exploiting this information.

PROCESSING THE DATA

Once the raw sensor measurements are collected, they must be made usable for satellite operators. To do this, it is first filtered, correlated and fused to maintain the orbital state vectors and their associated uncertainties.

Advanced orbit determination, propagation and covariance (uncertainty) management techniques are then applied to predict future object positions and potential close approaches. Screening criteria are based on the probability of collision, which accounts for satellite miss-distances and the uncertainties in the data used. However, one of the difficulties is that special perturbation (highly accurate) data, as well as most owner/operator ephemeris and third-party data, do not include realistic covariances that accurately represent the data’s accuracy.

To mitigate these concerns, synthetic covariance can be introduced. Covariance represents the accuracy of the satellite’s orbit. The synthetic covariance of the orbit is generated by comparing variations in the ephemeris over time. By performing synthetic covariance, it empirically provides an estimate of the orbit uncertainties consistent with the orbit ephemeris. The use of synthetic covariance also addresses cases in which SP data and some third-party data are missing. The empirical technique accounts for potential unknown/unreported maneuvers in the data. Together with the orbit ephemeris and the synthetic covariance, this represents a consistent dataset that can be used for collision avoidance screening, providing realistic risks and information for effective decision-making.

The resulting actionable products include conjunction warnings, collision risk metrics (such as collision probability) and recommended mitigation actions, for example, collision avoidance maneuvers. SDA and other organizations play a key operational role by facilitating data sharing and coordination between satellite operators, especially in time-critical situations.

DATA FRAGMENTATION

The emergence of multiple companies offering SSA services now means that there is a huge amount of data available, with many operators feeling that there is almost too much and are unsure which to trust. While the amount of data gathered is a positive and demonstrates how far we have come in terms of SSA, data fragmentation is a recognized concern, as isolated or proprietary datasets can lead to incomplete or inconsistent situational awareness.

From the SDA perspective, data sharing, standardization and trusted collaboration between operators are essential to building a coherent and reliable picture of the space environment. The overall trend is moving toward greater interoperability and coordination between commercial, institutional and international SSA actors, rather than relying on isolated or siloed solutions.

SSA AND STM: A COORDINATED APPROACH

Sensor data from both radar and optical sensors is critical, enabling SDA to fill in the gaps and understand how space objects behave, thereby making predictions about their orbital movements. Advancements in the quality and resolution of this data will help to ensure that, as the orbits become even more crowded, our knowledge of the bigger picture is better than it’s ever been.

However, the onus is on the space community as a whole to take the initiative and ensure that the orbital environment remains sustainable. Already, since 1957, when Sputnik was launched, we find ourselves at a tipping point, where the sheer number of objects in orbit threatens the space environment.

For operators, it is critical that ephemeris data is shared to provide access to a pool of data that can be used to promote spaceflight safety. Ensuring access to space data via trusted platforms such as the Space Safety Portal (SSP) will give operators access to improved conjunction screening and collision avoidance detection, data partners to improve data latency and data gaps, advanced cybersecurity and data security functionality.

The SDA and SSP occupy a unique position as a non-partisan, non-commercial platform that provides essential data conversion and reformatting, data fusion and single-tier collision avoidance monitoring. It can act as a central point for the reception, processing and dissemination of essential information for stakeholders: civil, commercial and military. Only through collaboration and the sharing of data can we ensure that space remains a sustainable, shared resource for future generations. We need to set that example today.