Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/121284
Citations
Scopus Web of Science® Altmetric
?
?
Type: Journal article
Title: Joint probabilistic data association and smoothing applied to multiple space object tracking
Author: Stauch, J.
Bessell, T.
Rutten, M.
Baldwin, J.
Jah, M.
Hill, K.
Citation: Journal of Guidance, Control, and Dynamics: devoted to the technology of dynamics and control, 2018; 41(1):19-33
Publisher: American Institute of Aeronautics and Astronautics
Issue Date: 2018
ISSN: 0731-5090
1533-3884
Statement of
Responsibility: 
Jason Stauch, Travis Bessell, Mark Rutten, Jason Baldwin, Moriba Jah and Keric Hill
Abstract: A foundational aspect of space domain awareness is the ability to identify and track space objects, including space object discovery and custody. This paper demonstrates the power of combining an efficient multiple hypothesis joint probabilistic data association (MH-JPDA) algorithm with a fixed-interval smoother to simultaneously track multiple space objects. For newly discovered objects, statistical initial orbit determination (SIOD) is possible with a single short optical tracklet, but results in large initial uncertainties. Combining these uncertainties with closely spaced objects can result in highly ambiguous data associations, which can lead to poor state estimates and even filter divergence. This paper invokes MH-JPDA to probabilistically update multiple tracks with multiple simultaneous observations in a sequential filter, while avoiding assigning one-to-one associations. Once sufficient information has been collected, the space objects become uniquely distinguishable among each other. Subsequently, the smoother is applied to achieve improved association of the prior observations. MH-JPDA allows for immediate track formation (using SIOD) and sequential processing of incoming observations, providing statistically rigorous real-time state estimates, whereas smoothing produces a more-refined, higher-confidence overall track estimate at user-defined intervals. This paper demonstrates this approach within the Constrained Admissible Region, Multiple Hypothesis Filter (CAR-MHF) software by tracking a simulated break-up scenario.
Rights: © 2017 by the American Institute of Aeronautics and Astronautics, Inc. The U.S. Government has a royalty-free license to exercise all rights under the copyright claimed herein for Governmental purposes. All other rights are reserved by the copyright owner. All requests for copying and permission to reprint should be submitted to CCC at www.copyright.com
DOI: 10.2514/1.G002230
Appears in Collections:Aurora harvest 4
Physics publications

Files in This Item:
File Description SizeFormat 
hdl_121284.pdfPublished version2.31 MBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.