Indian space intelligence startup Digantara launched MOSAIC, an AI-powered optical sensor network designed to track objects and debris in Low Earth Orbit. Featuring five initial autonomous nodes, the system delivers real-time orbital intelligence, helping satellite operators and civil authorities prevent space collisions and strengthen sovereign tracking capabilities.
BENGALURU, India — Indian space situational awareness and defence intelligence company Digantara launched MOSAIC, an artificial intelligence-powered wide-area optical sensor network engineered to search, detect, and track objects in Low Earth Orbit (LEO). The initial rollout deploys five autonomous sensor nodes designed to deliver real-time space domain awareness.
The deployment marks a major shift toward independent tracking capabilities as orbital congestion surges. By processing image data on edge hardware, the system reduces reliance on foreign space surveillance systems and helps protect critical satellites from collisions with space debris.
Technical Architecture and Orbital Capabilities
The MOSAIC architecture combines ground-based optical tracking units with edge computing systems. Each node features an Optical Head Unit paired with an Electronics Head Unit that runs onboard AI algorithms for immediate data analysis.
Autonomous Attitude Estimation: The network employs "Lost-in-Space" positioning algorithms to identify and catalog untracked space objects without requiring prior orbital trajectory data.
Resilient Infrastructure: Nodes run on solar power with integrated battery backups, engineered to endure harsh climatic environments ranging from high-temperature desert regions to sub-zero high-altitude locations.
Multi-Target Detection: Integrated machine learning models track stars and Resident Space Objects (RSOs) simultaneously, cataloging active satellites alongside faint orbital debris.
Impact on Satellite Operators, Defense, and Space Safety
Rapid expansion in commercial megaconstellations has heightened collision risks in LEO. Precise orbital tracking allows satellite operators to plan avoidance maneuvers, safeguarding commercial communications, remote sensing assets, and scientific missions.
For defense and civil space agencies, autonomous observation networks provide continuous space domain monitoring. The system reduces blind spots in orbital tracking maps while offering dual-use applications, such as celestial navigation support in environments where satellite GPS signals are disrupted or denied.
Official Statements and Sourcing
Official statements released by company leadership underscore the network's role in global orbital tracking infrastructure:
According to statements from Digantara:
"MOSAIC is what owning that capability looks like. Every big infrastructure problem eventually stops being about having one perfect system and starts being about having many resilient ones."
Digantara Founder and Chief Executive Officer Anirudh Sharma stated during the unveiling:
"We aim to deploy such sensors globally to maintain independent tracking and cataloguing of objects in orbit."
Why It Matters
As low Earth orbit grows increasingly crowded, operators face higher operational risks from untracked orbital fragments. Conventional tracking networks often struggle with low-visibility objects or updates delayed by centralized processing pipelines.
By executing real-time detection directly on edge nodes, networks like MOSAIC decrease tracking latency and expand global catalog coverage. This localized intelligence strengthens orbital traffic management frameworks, keeping commercial and sovereign assets safe in space.
Key Facts at a Glance
Developer: Digantara (Bengaluru, India).
System Name: MOSAIC (AI-Powered Wide Area Sensing Architecture).
Initial Deployment: Five interconnected, solar-powered sensor nodes.
Primary Target: Resident Space Objects (RSOs) and orbital debris in Low Earth Orbit (LEO).
Core Technology: AI optical imaging units with onboard Lost-in-Space processing.
Frequently Asked Questions
What is Digantara's MOSAIC network?
MOSAIC is an AI-driven ground network of optical sensors designed to detect, track, and catalog objects in Low Earth Orbit in real time.
How does the system detect objects without prior data?
The network uses onboard "Lost-in-Space" attitude estimation algorithms, enabling it to calculate the position and trajectory of unknown space objects instantly.
Why is tracking objects in Low Earth Orbit important?
Thousands of defunct satellites and fragments orbit Earth at high speeds. Accurate tracking helps operators prevent orbital collisions that could damage active space infrastructure.
Source: Official press releases and announcements from Digantara.