Real‐Time Thermospheric Density Estimation via Two‐Line Element Data Assimilation
Inaccurate estimates of the thermospheric density are a major source of error in low Earth orbit prediction. In this work, we develop a reduced-order dynamic model for the thermospheric density by computing the main spatial modes of the atmosphere and deriving a linear model for the dynamics. This m...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
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American Geophysical Union (AGU)
2021
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| Online Access: | https://hdl.handle.net/1721.1/135442 |
| _version_ | 1826215813063901184 |
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| author | Gondelach, David J Linares, Richard |
| author2 | Massachusetts Institute of Technology. Department of Aeronautics and Astronautics |
| author_facet | Massachusetts Institute of Technology. Department of Aeronautics and Astronautics Gondelach, David J Linares, Richard |
| author_sort | Gondelach, David J |
| collection | MIT |
| description | Inaccurate estimates of the thermospheric density are a major source of error in low Earth orbit prediction. In this work, we develop a reduced-order dynamic model for the thermospheric density by computing the main spatial modes of the atmosphere and deriving a linear model for the dynamics. This model is then used to estimate the density using two-line element (TLE) data by simultaneously estimating the reduced-order modes and the orbits and ballistic coefficients of several objects using an unscented Kalman filter. Accurate density estimation using the TLEs of 15 objects is demonstrated and validated against CHAMP and GRACE accelerometer-derived densities. Finally, the use of the model for density forecasting is shown. |
| first_indexed | 2024-09-23T16:37:09Z |
| format | Article |
| id | mit-1721.1/135442 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T16:37:09Z |
| publishDate | 2021 |
| publisher | American Geophysical Union (AGU) |
| record_format | dspace |
| spelling | mit-1721.1/1354422023-03-24T19:10:40Z Real‐Time Thermospheric Density Estimation via Two‐Line Element Data Assimilation Gondelach, David J Linares, Richard Massachusetts Institute of Technology. Department of Aeronautics and Astronautics Inaccurate estimates of the thermospheric density are a major source of error in low Earth orbit prediction. In this work, we develop a reduced-order dynamic model for the thermospheric density by computing the main spatial modes of the atmosphere and deriving a linear model for the dynamics. This model is then used to estimate the density using two-line element (TLE) data by simultaneously estimating the reduced-order modes and the orbits and ballistic coefficients of several objects using an unscented Kalman filter. Accurate density estimation using the TLEs of 15 objects is demonstrated and validated against CHAMP and GRACE accelerometer-derived densities. Finally, the use of the model for density forecasting is shown. 2021-10-27T20:23:29Z 2021-10-27T20:23:29Z 2020 2021-05-05T18:40:30Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/135442 en 10.1029/2019SW002356 Space Weather Creative Commons Attribution 4.0 International license https://creativecommons.org/licenses/by/4.0/ application/pdf American Geophysical Union (AGU) American Geophysical Union (AGU) |
| spellingShingle | Gondelach, David J Linares, Richard Real‐Time Thermospheric Density Estimation via Two‐Line Element Data Assimilation |
| title | Real‐Time Thermospheric Density Estimation via Two‐Line Element Data Assimilation |
| title_full | Real‐Time Thermospheric Density Estimation via Two‐Line Element Data Assimilation |
| title_fullStr | Real‐Time Thermospheric Density Estimation via Two‐Line Element Data Assimilation |
| title_full_unstemmed | Real‐Time Thermospheric Density Estimation via Two‐Line Element Data Assimilation |
| title_short | Real‐Time Thermospheric Density Estimation via Two‐Line Element Data Assimilation |
| title_sort | real time thermospheric density estimation via two line element data assimilation |
| url | https://hdl.handle.net/1721.1/135442 |
| work_keys_str_mv | AT gondelachdavidj realtimethermosphericdensityestimationviatwolineelementdataassimilation AT linaresrichard realtimethermosphericdensityestimationviatwolineelementdataassimilation |