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

Accurately modeling the density of atmospheric mass is critical for orbit determination and prediction space objects. Existing models (ADMs) have an accuracy about 15%. Developing high-precision ADMs a long-term goal that requires better understanding characteristics, more accurate methods, improved spatiotemporal data. This study proposes method calibrating using sparse angular data objects in low-Earth over certain period time. Applying corrected ADM not only improves determination, but also enhances beyond correction period. The compares impact two calibration methods: model coefficient (ADMC) high precision satellite drag (HASDM) on One month ground-based telescope array used to validate results. Space are classified as objects, participating calibration, verification inside outside region, respectively. results show applying calibrated can significantly increase prediction. For within object’s error was reduced by 55%, while 45%. reduction this region 30%. proposed contributes development reliable with provide significant academic value field situational awareness.