# Improving Low Earth Orbit (LEO) Prediction with Accelerometer Data
## 6 Discussions  
This article aimed at investigating centimeter level precision of LEO orbit prediction for real time applications. It is a good replacement of using accelerometer data instead of empirical force models when conducting LEO orbit prediction. Three strategies with estimation of different dynamic parameters were conducted. The results show that with our proposed method, the LEO orbit precision could reach the centimeter level and even predicting within two hours. Two more practical issues should be clarified. Figure 12: RMS values of LEO orbits for the along-track, cross-track, and radial direction for another one hour and corresponding URE values. The first one is the feasibility of widespread use of accelerometers. The idea of using accelerometers for orbit prediction is a good idea and it was already shown in this study. However, the accelerometers we used were of high quality for specific missions, such as a gravity mission. Such accelerometers may be too expensive for the mass market. Concerning this issue, experiments (one can add colored or white noise in the accelerometer data) could be conducted in the future to check the tolerance of accelerometer data with respect to the precision of orbit prediction. The second issue is the time gap of LEO onboard observation data collection. We took GRACE-A as example, which has an inclination of 89\({}^{\circ}\). It is quite easy to have a continuous coverage for sustained period (half cycle of the LEO orbital period) where the uplink and downlink station are located at high latitudes (north and south). However, more uplink and downlink stations are needed of LEO satellites with low orbital inclination to meet the max length of the LEO orbit prediction (such as about 20 min for GRACE-A to keep the centimeter precision of the orbit prediction with empirical models). The distribution of the uplink and downlink stations for different inclinations of LEO satellites should be investigated to guarantee the time gap of onboard data collection. All authors contributed to the writing of this manuscript. [PERSON], [PERSON], and [PERSON] conceived the idea of employing accelerometer data to conduct LEO orbit prediction. [PERSON] and [PERSON] processed the data and investigated the results. [PERSON], [PERSON], and [PERSON] validated the data. All authors have read and agreed to the published version of the manuscript. This study is sponsored by National Natural Science Foundation of China (41874030), The Scientific and Technological Innovation Plan from Shanghai Science and Technology Committee (18511101801), and The National Key Research and Development Program of China (2017 YFA0603102), and the Fundamental Research Funds for the Central Universities. Thanks to Physical Oceanography Distributed Active Archive Center (PO. DAAC) of JPL for providing the raw GNSS observations and post-processed reduced dynamic orbit of GRACE-A and GRACE-C. The GNSS observations and orbit products are available from [[https://podaac-tools.jpl.nasa.gov/drive/files/allData/grace/L1B/IPL](https://podaac-tools.jpl.nasa.gov/drive/files/allData/grace/L1B/IPL)]([https://podaac-tools.jpl.nasa.gov/drive/files/allData/grace/L1B/IPL](https://podaac-tools.jpl.nasa.gov/drive/files/allData/grace/L1B/IPL)) and [[https://podaac-tools.jpl.nasa.gov/drive/files/allData/grace/L1B/IPL/RL04/ASCII](https://podaac-tools.jpl.nasa.gov/drive/files/allData/grace/L1B/IPL/RL04/ASCII)]([https://podaac-tools.jpl.nasa.gov/drive/files/allData/grace/L1B/IPL/RL04/ASCII](https://podaac-tools.jpl.nasa.gov/drive/files/allData/grace/L1B/IPL/RL04/ASCII)) for GRACE-A and GRACE-C, respectively. We are also grateful to CODE and GFZ real time group for providing precise GPS final products and real time products, respectively. The authors declare no conflict of interest. The following acronyms and abbreviations are used in this manuscript: