# Real‐Time Thermospheric Density Estimation via Two‐Line Element Data Assimilation

@article{Gondelach2020RealTimeTD, title={Real‐Time Thermospheric Density Estimation via Two‐Line Element Data Assimilation}, author={David J. Gondelach and Richard Linares}, journal={Space Weather}, year={2020}, volume={18} }

Inaccurate estimates of the thermospheric density are a major source of error in low Earth orbit prediction. Therefore, real‐time density estimation is required to improve orbit prediction. In this work, we develop a dynamic reduced‐order model for the thermospheric density that enables real‐time density estimation using two‐line element (TLE) data. For this, the global thermospheric density is represented by the main spatial modes of the atmosphere and a time‐varying low‐dimensional state and…

## 16 Citations

Real‐Time Thermospheric Density Estimation via Radar and GPS Tracking Data Assimilation

- PhysicsSpace Weather
- 2021

As the number of man‐made Earth‐orbiting objects increases, satellite operators need enhanced space traffic management capabilities to ensure safe space operations. For objects in Low Earth orbit,…

A Framework to Estimate Local Atmospheric Densities With Reduced Drag‐Coefficient Biases

- Environmental ScienceSpace Weather
- 2022

An accurate estimation of upper atmospheric densities is crucial for precise orbit determination (POD), prediction of low Earth orbit satellites, and scientific studies of the Earth's atmosphere. But…

Evaluation of Physics‐Based Data Assimilation System Driven by Neutral Density Data From a Single Satellite

- Physics, Environmental ScienceSpace Weather
- 2020

Accurate forecast of the thermospheric density is critical to the space community. The data assimilation approach that is based on the self‐consistent upper‐atmosphere model may provide better…

Qualitative and Quantitative Assessment of the SET HASDM Database

- PhysicsSpace Weather
- 2021

The High Accuracy Satellite Drag Model (HASDM) is the operational thermospheric density model used by the US Space Force Combined Space Operations Center. By using real‐time data assimilation, HASDM…

Machine‐Learned HASDM Thermospheric Mass Density Model With Uncertainty Quantification

- Computer ScienceSpace Weather
- 2022

A thermospheric neutral mass density model with robust and reliable uncertainty estimates is developed based on the Space Environment Technologies (SET) High Accuracy Satellite Drag Model (HASDM) density database, and a storm‐time comparison shows that HASDM‐ML also supplies meaningful uncertainty estimates during extreme geomagnetic events.

Atmospheric Density Uncertainty Quantification for Satellite Conjunction Assessment

- PhysicsAIAA Scitech 2020 Forum
- 2020

Conjunction assessment requires knowledge of the uncertainty in the predicted orbit. Errors in the atmospheric density are a major source of error in the prediction of low Earth orbits. Therefore,…

A long-range forecasting model for the thermosphere based on the intelligent optimized particle filtering

- PhysicsScience China Earth Sciences
- 2021

The uncertainties associated with the variations in the thermosphere are responsible for the inaccurate prediction of the orbit decay of low Earth orbiting space objects due to the drag force.…

Uncertainty quantification techniques for data-driven space weather modeling: thermospheric density application

- Environmental ScienceScientific reports
- 2022

Machine learning (ML) has been applied to space weather problems with increasing frequency in recent years, driven by an influx of in-situ measurements and a desire to improve modeling and…

Uncertainty Quantification Techniques for Space Weather Modeling: Thermospheric Density Application

- Environmental ScienceArXiv
- 2022

Two techniques to develop nonlinear ML regression models to predict thermospheric density while providing robust and reliable uncertainty estimates are proposed: Monte Carlo (MC) dropout and direct prediction of the probability distribution, both using the negative logarithm of predictive density (NLPD) loss function.

Decorrelating density and drag-coefficient through attitude variations

- Environmental Science
- 2021

An accurate estimation of upper atmospheric densities is crucial for precise orbit determination and prediction of low Earth orbit (LEO) satellites as well as scientific studies of the Earth’s…

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