Reduced order probabilistic emulation for physics‐based thermosphere models

RJ Licata, PM Mehta - Space Weather, 2023 - Wiley Online Library
The geospace environment is volatile and highly driven. Space weather has effects on
Earth's magnetosphere that cause a dynamic and enigmatic response in the thermosphere …

[HTML][HTML] A novel stochastic unscented transform for probabilistic drag modeling and conjunction assessment

R Bhatia, GJR Santos, JD Griesbach, PM Mehta - Acta Astronautica, 2025 - Elsevier
Abstract Space safety and sustainability has recently received formalized recognition in the
light of proliferation by large satellite constellations operated by the commercial sector …

A Case Study on the Effect of Atmospheric Density Calibration on Orbit Predictions with Sparse Angular Data

J Chen, J Sang, Z Li, C Liu - Remote Sensing, 2023 - mdpi.com
Accurately modeling the density of atmospheric mass is critical for orbit determination and
prediction of space objects. Existing atmospheric mass density models (ADMs) have an …

Probabilistic short‐term solar driver forecasting with neural network ensembles

JD Daniell, PM Mehta - Space Weather, 2024 - Wiley Online Library
Abstract Space weather indices are used to drive forecasts of thermosphere density, which
directly affects objects in low‐Earth orbit (LEO) through atmospheric drag force. A set of …

[PDF][PDF] Probabilistic Space Weather Modeling and its Impact on Space Situational Awareness and Space Traffic Management

S Paul, P Mehta, T Kelecy, R Coder - Proceedings of the Advanced …, 2023 - amostech.com
The uncertainty in a Low Earth Orbit (LEO) space object's future position is influenced by
uncertainty in thermospheric density, which can vary significantly during active space …

Artificial Intelligence for a Safe Space: Data and Model Development Trends in Orbit Prediction and Collision Avoidance

G Choumos, K Tsaprailis, V Lappas… - AIAA SCITECH 2024 …, 2024 - arc.aiaa.org
The importance of safety in space has been greatly emphasized during the recent years as a
result of the continuous technological advancements, leading to the reduction of launch …

[PDF][PDF] A Novel Stochastic Unscented Transform for Robust State Estimation Enabling Enhanced Space Domain Awareness

GJR Santos, JD Griesbach, R Bhatia, PM Mehta - 2024 - amostech.com
ABSTRACT IARPA's SINTRA program challenge to detect and track lethal non-trackable
(LNT) objects is crucial for mitigating collision risks and maintaining the safety of space …

[PDF][PDF] Sources of uncertainty in drag modeling and its effect on predicted stated covariance

J Daniell, M Piyush - 2023 - par.nsf.gov
Realism of the predicted or forecasted orbital state covariance are crucial for several aspects
of space traffic management and space domain awareness including sensor tasking …