Modeling the position and velocity distribution of space objects by maximizing entropy with energy constraint

Abstract

In this work, we have developed a 6-dimensional joint probability density function for the 3-dimensional position and 3-dimensional velocity vectors of space objects in the Low Earth Orbit (LEO) based on the Principle of Maximum Entropy (MaxEnt), adhering to the principle of energy conservation. For the problem under consideration, maximizing entropy subject to energy conservation ensures that the derived probability density function (PDF) is the best representation of the uncertainty of a space object while the sampled position and velocity vectors from the PDF adhere to the orbital dynamics. We approach the entropy maximization by constructing a Lagrangian functional incorporating the energy conservation constraint and the normalization constraint of the PDF using Lagrange multipliers, setting the functional derivative of the Lagrangian to zero. This PDF can be used to generate position and velocity samples for space objects without any prior assumption and can further be utilized for orbital uncertainty propagation either using the Monte-Carlo method or by direct propagation of the PDF through the Fokker-Planck Equation.