Probabilistic Methods for Initial Orbit Determination and Orbit Determination in Cislunar Space

Fuente: arXiv
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Autori principali: Paranjape, Ishan, Hejmadi, Tarun, Chakravorty, Suman
Natura: Preprint
Pubblicazione: 2026
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author Paranjape, Ishan
Hejmadi, Tarun
Chakravorty, Suman
author_facet Paranjape, Ishan
Hejmadi, Tarun
Chakravorty, Suman
contents In orbital mechanics, Gauss's method for orbit determination (OD) is a popular, minimal assumption solution for obtaining the initial state estimate of a passing resident space object (RSO). Since much of the cislunar domain relies on three-body dynamics, a key assumption of Gauss's method is rendered incompatible, creating a need for a new, minimal assumption method for initial orbit determination (IOD). In this work, we present a framework for short and long term probabilistic target tracking in cislunar space which produces an initial state estimate with as few assumptions as possible. Specifically, we propose an IOD method involving the kinematic fitting of several series of noisy, consecutive ground-based observations. Once a probabilistic initial state estimate in the form of a particle cloud is formed, we apply the powerful Particle Gaussian Mixture (PGM) Filter to reduce the uncertainty of our state estimate over time. This combined IOD/OD framework is demonstrated for several classes of trajectories in cislunar space and compared to better-known filtering frameworks.
format Preprint
id arxiv_https___arxiv_org_abs_2602_18058
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Probabilistic Methods for Initial Orbit Determination and Orbit Determination in Cislunar Space
Paranjape, Ishan
Hejmadi, Tarun
Chakravorty, Suman
Earth and Planetary Astrophysics
Instrumentation and Methods for Astrophysics
Systems and Control
Optimization and Control
Data Analysis, Statistics and Probability
Space Physics
Applications
In orbital mechanics, Gauss's method for orbit determination (OD) is a popular, minimal assumption solution for obtaining the initial state estimate of a passing resident space object (RSO). Since much of the cislunar domain relies on three-body dynamics, a key assumption of Gauss's method is rendered incompatible, creating a need for a new, minimal assumption method for initial orbit determination (IOD). In this work, we present a framework for short and long term probabilistic target tracking in cislunar space which produces an initial state estimate with as few assumptions as possible. Specifically, we propose an IOD method involving the kinematic fitting of several series of noisy, consecutive ground-based observations. Once a probabilistic initial state estimate in the form of a particle cloud is formed, we apply the powerful Particle Gaussian Mixture (PGM) Filter to reduce the uncertainty of our state estimate over time. This combined IOD/OD framework is demonstrated for several classes of trajectories in cislunar space and compared to better-known filtering frameworks.
title Probabilistic Methods for Initial Orbit Determination and Orbit Determination in Cislunar Space
topic Earth and Planetary Astrophysics
Instrumentation and Methods for Astrophysics
Systems and Control
Optimization and Control
Data Analysis, Statistics and Probability
Space Physics
Applications
url https://arxiv.org/abs/2602.18058