Impact Factor
Call For Paper
Volume 12 Issue 07
July 2026
Author(s)
Abstract
The Rapid Increase In Satellite Launches And Orbital Debris Has Raised Critical Challenges In Ensuring Collision-free Operations And Efficient Launch Scheduling. ISO-AI Lite Is A Lightweight, Explainable Artificial Intelligence Pipeline Designed To Assist In Launch-window Validation, Conjunction Risk Assessment, And Minimal Avoidance Manoeuvre Planning. The System Takes Two-Line Element (TLE) Data Of A Satellite And A Potential Conjunction Object As Input, Propagates Their Orbits Using The SGP4 Model, And Estimates The Probability Of Collision (PoC) Through Both Analytical And Monte Carlo Methods. It Integrates A Simple Weather Constraint Checker To Validate Launch Feasibility Based On Basic Environmental Parameters. When A High-risk Conjunction Is Detected, The Model Suggests An Optimal, Low-cost Avoidance Manoeuvre, Preferably In The Along-track Direction, Ensuring Both Safety And Fuel Efficiency. Additionally, The Framework Includes An Optional Single-sensor Re-observation Module That Refines Orbital Uncertainty Through A Kalman-based Update Before Executing The Manoeuvre. The Overall Objective Of ISO-AI Lite Is To Demonstrate A Compact, Interpretable, And Cost-effective Decision-support Tool For Mission Operators And Students, Enabling Improved Situational Awareness, Risk Mitigation,
Keywords
Paper ID
IJSARTV12I3104797
Publication Date
March 28, 2026
Research Area
Artificial Intelligence For Space Application