Stochastic Satellite Air Drag with the Ballistic Coefficient as a Random Variable

Abstract

The drag acceleration caused by the Earth's atmosphere is a significant cause of prediction uncertainty for low Earth orbit satellites. Most existing research has focused on improving deterministic atmospheric density predictions or on density as a random variable. This research investigates a new paradigm and focuses on modeling the uncertainty caused by air drag using the ballistic coefficient, a component of air drag that is independent of the model used to predict atmospheric density. Time series of ballistic coefficient values are calculated and analyzed as random processes. These random processes are then used as the foundation of a stochastic satellite prediction model that calculates the parameters of the random process and predicts satellite orbits with realistic uncertainty. The model is developed using the Unscented Transform and is validated using Monte Carlo simulation and empirical analysis, and proves effective for any choice of atmospheric density model and a variety of dynamical formulations.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2021
Accession Number
AD1148773

Entities

People

  • Everett B. Iv Palmer

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Space

DTIC Thesaurus Topics

  • Air Force
  • Artificial Satellites
  • Astronautics
  • Celestial Mechanics
  • Computational Science
  • Data Science
  • Earth Orbits
  • Information Science
  • Kalman Filters
  • Knowledge Management
  • Low Earth Orbits
  • Mathematical Filters
  • Monte Carlo Method
  • Random Variables
  • Satellite Orbits
  • Space Debris
  • Space Objects
  • Spacecraft
  • Spacecraft Orbits
  • Statistical Algorithms
  • Surveys

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Aerospace Engineering.
  • Computational Modeling and Simulation

Technology Areas

  • Space
  • Space - Orbital Debris