Reachability Analysis Based Tracking: Applications to Non-cooperative Space Object Tracking

Zach Hall, Puneet Singla

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

This paper presents a reachability set based method for tracking maneuvering space objects in the presence of sparse measurements. The proposed approach invokes the Dynamic Data Driven Application Systems (DDDAS) paradigm by dynamically integrating model forecasts due to uncertainties in maneuver capabilities with collected sensor data to search and track for a non-cooperative satellite in a control theoretic framework. The typically large time interval between measurements from ground stations presents significant problems for tracking satellites that have maneuvered during this interval. Using reachability set propagation techniques and a particle filter update scheme, an intelligently guided search algorithm is developed. This algorithm enables the systematic reduction of likely reachable states until measurements of the target are acquired and traditional tracking techniques can be resumed. Numerical simulations of a space-based sensor tasking scenario are given, however, the method is generic and can be extended to ground-based sensors or a combination of both ground and space-based sensors.

Original languageEnglish (US)
Title of host publicationDynamic Data Driven Application Systems - Third International Conference, DDDAS 2020, Proceedings
EditorsFrederica Darema, Erik Blasch, Sai Ravela, Alex Aved
PublisherSpringer Science and Business Media Deutschland GmbH
Pages200-207
Number of pages8
ISBN (Print)9783030617240
DOIs
StatePublished - 2020
Event3rd International Conference on Dynamic Data Driven Application Systems, DDDAS 2020 - Boston, United States
Duration: Oct 2 2020Oct 4 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12312 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd International Conference on Dynamic Data Driven Application Systems, DDDAS 2020
Country/TerritoryUnited States
CityBoston
Period10/2/2010/4/20

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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