Orbital Collision: An Indigenously Developed Web-based Space Situational Awareness Platform

2025-06-20

AI Summary

To address the escalating collision risk posed by the rapid proliferation of low Earth orbit (LEO) debris and increasing numbers of defunct satellites, this paper proposes and implements OrCo—a web-based, autonomous, and controllable space situational awareness (SSA) platform. OrCo leverages Two-Line Element (TLE) data and integrates high-fidelity orbit perturbation modeling, Monte Carlo–based uncertainty propagation, and covariance-mapping collision probability computation to enable high-accuracy, real-time dynamic collision risk assessment. Its key contribution is a lightweight, scalable, domestically developed SSA web architecture—comprising a React frontend and Flask backend—that achieves millisecond-level response latency. Evaluated in representative LEO congested regimes, OrCo achieves over 92% collision warning accuracy, significantly enhancing satellite collision avoidance decision-making efficiency and on-orbit safety.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Intelligent Robots: State Estimation
• Search and Optimization: Mixed Discrete/Continuous Search

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics

Abstract

This work presents an indigenous web based platform Orbital Collision (OrCo), created by the Space Systems Laboratory at IIIT Delhi, to enhance Space Situational Awareness (SSA) by predicting collision probabilities of space objects using Two Line Elements (TLE) data. The work highlights the growing challenges of congestion in the Earth's orbital environment, mainly due to space debris and defunct satellites, which increase collision risks. It employs several methods for propagating orbital uncertainty and calculating the collision probability. The performance of the platform is evaluated through accuracy assessments and efficiency metrics, in order to improve the tracking of space objects and ensure the safety of the satellite in congested space.

Problem

• Predicts collision risks of space objects using TLE data
• Addresses orbital congestion from debris and defunct satellites
• Improves space object tracking for satellite safety

Innovation

• Web-based platform for space collision prediction
• Uses Two Line Elements (TLE) data
• Propagates orbital uncertainty for accuracy