Digantara: Building India’s Orbital Traffic and Space-Threat Intelligence Network

Digantara is developing an indigenous space-domain-awareness system to detect, track, characterise and predict the movement of satellites, spent rocket stages and orbital debris. The Bengaluru-based company combines surveillance satellites, ground observatories, optical and LiDAR payloads, orbit-determination software and defence-oriented analytics within a unified architecture called AIRA.

As satellite deployments increase, operators need accurate knowledge of every resident space object near their spacecraft. Even a small fragment travelling at orbital velocity can damage a satellite, while an unidentified manoeuvre by another spacecraft may represent a safety risk or strategic activity. Digantara’s system is designed to convert observations from multiple sensors into updated trajectories, collision assessments and operational warnings.

AIRA Intelligence Architecture

AIRA forms the core processing and data-fusion layer of Digantara’s network. It receives measurements from space-based sensors, ground observatories and compatible external feeds, then processes them through the company’s Or-Eng orbit engine.

The platform is designed to integrate optical, infrared, radar and LiDAR-derived data without depending on a single sensor type. Cross-verifying observations from different sources improves object identification, filters measurement noise and reduces uncertainty in orbital predictions. Digantara states that AIRA can support tracking from low Earth orbit to geostationary orbit and can expand towards cislunar surveillance.

The company reports a minimum object-detection scale of approximately three centimetres across its broader architecture, data latency below five minutes and revisit rates reaching eight observations per day for selected targets. These are company-stated system metrics whose operational performance will vary with orbit, sensor availability, illumination and observing geometry.

Space-Based Surveillance

Ground telescopes are constrained by weather, daylight, atmospheric distortion, geography and local viewing angles. Space-based sensors can observe orbital objects from a different geometry and maintain custody of targets that may pass outside a ground network’s field of view.

Digantara is developing satellites in the 25–150-kilogram class equipped with optical and LiDAR sensors for space-to-space tracking. These spacecraft are intended to detect fast-moving objects, collect high-resolution observations and transmit measurements into AIRA for orbit calculation and catalogue maintenance.

Its SCOT spacecraft—Space Camera for Object Tracking—provides an operational foundation for this approach. Digantara states that SCOT has been integrated into AIRA’s data stream after obtaining its first raw image above South America, adding an orbital observation source to the company’s ground-based network.

Space-based surveillance allows the observing satellite to view another spacecraft against the cold background of space. This can support detection of faint targets, close-range characterisation and more frequent tracking of objects in low Earth orbit.

PRISM Optical Payloads

PRISM is Digantara’s flight-proven electro-optical sensor family. It combines low-light optics with onboard processing to image fast or faint orbital targets using short exposure times that limit motion blur.

The PRISM Wide configuration uses a 48-millimetre aperture and a 26-degree field of view for wide-area surveillance and rendezvous support. PRISM Sharp uses a 180-millimetre aperture and a narrower five-degree field of view for high-resolution observation and long-distance object custody.

These payloads can support resident-space-object detection, catalogue building, object characterisation, autonomous navigation and imaging during rendezvous or proximity operations.

PULSE LiDAR System

PULSE combines optical imaging with LiDAR-based depth measurement. Its photon-sensitive detectors are designed to measure spatial structure and distance while observing objects in relative motion.

The system is offered in configurations intended for ranges from about five to 100 kilometres. Short-range versions can support proximity operations, while longer-range variants are designed for precision tracking and rendezvous missions.

Combining imagery with depth information can improve estimates of an object’s position, dimensions, configuration and relative movement. This is valuable when two spacecraft are approaching each other or when an operator needs to inspect an unknown object.

Ground-Based Sensor Network

Digantara’s ground segment consists of remotely taskable observatories that scan orbital regions and track selected targets. The company lists ten active observatories with coverage extending from low Earth orbit to geostationary orbit and stated angular tracking precision of one arcsecond or better.

A distributed network allows the same object to be observed from different geographical locations. These measurements can be combined to improve orbit determination and maintain tracking continuity as the object moves across the sky.

Ground sensors remain particularly useful for persistent catalogue maintenance, monitoring higher orbital regimes and cross-validating observations obtained by spacecraft.

Converting Observations into Orbits

Raw telescope images often show orbital objects as streaks against a star field. Digantara’s Or-Eng processing system detects these streaks, associates them with known objects and estimates their trajectories.

The resulting products can include Two-Line Element sets, Orbit Parameter Messages and Orbit Ephemeris Messages. These formats describe an object’s orbit, state vector and predicted position over time. Covariance data expresses the uncertainty surrounding each estimate, allowing operators to judge the reliability of a collision warning.

LOCUS, Digantara’s tracking-data service, performs orbit determination, propagation, ephemeris generation, uncertainty analysis and correlation of untracked objects. It can also support satellite-deployment verification and maintenance of independent orbital catalogues.

Identifying and Characterising Objects

IRIS is Digantara’s non-Earth imaging and object-characterisation service. Instead of photographing the Earth, its sensors observe other satellites and debris.

The system is designed to determine an object’s approximate size, geometry, orientation, pointing direction and tumble rate. It can also associate radio-frequency characteristics with a satellite and generate updated orbital state vectors.

Such information helps distinguish an operational spacecraft from an inactive object, identify configuration changes and assess whether unusual movement is intentional, accidental or linked to a malfunction.

Collision Assessment and Manoeuvre Planning

A conjunction occurs when two orbital objects are predicted to pass close to each other. The risk depends on their relative velocity, positional uncertainty and miss distance.

Digantara’s MAP platform screens spacecraft against tracked objects, assesses collision probability and calculates avoidance manoeuvres. It also supports mission design, early-orbit operations, station-keeping, pass prediction, de-orbit planning and rendezvous missions.

The company states that MAP can generate conjunction alerts in under 15 seconds and manoeuvre recommendations in under four minutes after receiving the required data. These figures represent stated platform performance and remain dependent on observation quality and the operational configuration used.

Rapid analysis is important because operators must evaluate whether a warning is credible, determine how a manoeuvre will affect the mission and coordinate commands before the predicted encounter.

Defence and Threat Monitoring

Orbital safety and national security increasingly use the same sensor data. A spacecraft approaching another satellite may be conducting inspection, servicing, intelligence collection or potentially hostile activity.

Digantara’s STARS platform is designed for space intelligence, surveillance and reconnaissance. It monitors activity within selected orbital regions, identifies surveillance blind spots, predicts satellite passes and examines the neighbourhood surrounding protected spacecraft.

Long-term pattern-of-life analysis allows the platform to establish a satellite’s normal behaviour and flag deviations such as unexpected manoeuvres, unusual proximity operations or changes in orbital routine. STARS can also model break-ups, deployments and hypothetical threat scenarios to support attribution and operational planning.

Its surveillance-network simulator evaluates sensor placement, tasking strategy, coverage and revisit performance before a physical network is deployed. This helps defence organisations identify where additional telescopes or orbital sensors would produce the greatest improvement.

Tracking Uncorrelated Objects

An uncorrelated target is an observation that cannot immediately be matched with an object in an existing catalogue. It may represent newly deployed hardware, fragmented debris or a spacecraft whose orbit has changed.

Digantara’s architecture correlates repeated measurements to determine whether such observations belong to the same object. Once sufficient data is available, the system can estimate an orbit, assign an identity and maintain continued custody.

Independent tracking is strategically important because public catalogues may contain delayed, incomplete or lower-precision information. A sovereign observation network allows India and partner organisations to verify orbital activity using their own sensors and analytical models.

Importance for India

India’s civil, commercial and defence satellites support communications, navigation, weather forecasting, reconnaissance, disaster management and financial infrastructure. Protecting these systems requires accurate knowledge of the surrounding orbital environment.

Digantara is creating an Indian capability that extends beyond satellite construction into surveillance, intelligence and operational decision support. Its system can assist satellite operators with collision avoidance while providing defence organisations with anomaly detection, behavioural analysis and orbital-threat assessment.

The company’s combination of in-orbit sensors, ground observatories and AIRA-based processing creates an integrated chain from detection to decision. It also builds domestic expertise in precision optics, LiDAR, orbital mechanics, artificial intelligence, spacecraft engineering and secure command software.

Digantara’s work positions India to maintain its own catalogue of satellites and debris, verify activity independently and protect spacecraft through faster orbital intelligence. As Earth’s orbital environment becomes more congested and strategically contested, such infrastructure will become central to safe spaceflight and national space security.

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REFERENCES

Digantara. “AIRA: The Foundation of Space Intelligence.”
https://www.digantara.co.in/aira

Digantara. “Space Intelligence, Surveillance and Data Infrastructure.” Official Website.
https://www.digantara.co.in/

Digantara. “PRISM: Electro-Optical Payload for Precision Space Observation.”
https://www.digantara.co.in/solutions/prism

Digantara. “PULSE: LiDAR-Based Imaging Payload for Dynamic Tracking.”
https://www.digantara.co.in/solutions/pulse

Digantara. “LOCUS: Resident Space Object Tracking and Orbit Propagation.”
https://www.digantara.co.in/solutions/locus

Digantara. “IRIS: Non-Earth Imaging and Space-Object Characterisation.”
https://www.digantara.co.in/solutions/iris

Digantara. “STARS: Space Intelligence, Surveillance and Reconnaissance Analytics.”
https://www.digantara.co.in/solutions/stars

Digantara. “MAP: Mission Assurance, Collision Assessment and Manoeuvre Planning.”
https://www.digantara.co.in/solutions/map

Digantara. “Space-Domain-Awareness Applications.”
https://www.digantara.co.in/solutions/applications

Startup India. “Digantara: Space Situational Awareness and Orbital Surveillance.”
https://www.startupindia.gov.in/nsa2022results/space.html

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