A new multi-target tracking algorithm for a large number of orbiting objects
A new multi-target tracking algorithm for a large number of orbiting objects
This paper demonstrates the applicability of the filter for Hypothesised and Independent Stochastic Populations (HISP), a multi-target joint detection/tracking algorithm derived from a recent estimation framework for stochastic populations, to wide area surveillance scenarios in the context of Space Situational Awareness. Designed for multi-object estimation problems where the data association between targets and collected observations is moderately ambiguous, the HISP filter has a linear complexity with the number of maintained tracks and the number of observations, and is a scalable filtering solution adapted to large-scale target tracking scenarios. It is illustrated on a challenging surveillance problem involving 30 targets on different orbits, observed by 3 sensors with limited coverage, measurement noise, false alarms, and missed detections.
2077-2096
Delande, E. D.
e17b3b32-0949-4914-801e-c9386bce39a5
Houssineau, J.
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Franco, J.
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Frueh, C.
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Clark, D. E.
537f80e8-cbe6-41eb-b1d4-31af1f0e6393
9 February 2017
Delande, E. D.
e17b3b32-0949-4914-801e-c9386bce39a5
Houssineau, J.
89988b62-a668-4560-b49f-c1686ba7b584
Franco, J.
6f88f0bd-effb-46a2-9a6f-a2062915786d
Frueh, C.
a1a80c71-5927-4247-be9a-2e11a75aea38
Clark, D. E.
537f80e8-cbe6-41eb-b1d4-31af1f0e6393
Delande, E. D., Houssineau, J., Franco, J., Frueh, C. and Clark, D. E.
(2017)
A new multi-target tracking algorithm for a large number of orbiting objects.
Sims, Jon A., Leve, Frederick A., McMahon, Jay W. and Guo, Yanping
(eds.)
In Spaceflight Mechanics 2017.
vol. 160,
Univelt, Inc.
.
Record type:
Conference or Workshop Item
(Paper)
Abstract
This paper demonstrates the applicability of the filter for Hypothesised and Independent Stochastic Populations (HISP), a multi-target joint detection/tracking algorithm derived from a recent estimation framework for stochastic populations, to wide area surveillance scenarios in the context of Space Situational Awareness. Designed for multi-object estimation problems where the data association between targets and collected observations is moderately ambiguous, the HISP filter has a linear complexity with the number of maintained tracks and the number of observations, and is a scalable filtering solution adapted to large-scale target tracking scenarios. It is illustrated on a challenging surveillance problem involving 30 targets on different orbits, observed by 3 sensors with limited coverage, measurement noise, false alarms, and missed detections.
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More information
Published date: 9 February 2017
Additional Information:
Funding Information:
Emmanuel Delande, Jose Franco, and Daniel Clark are supported by the Engineering and Physical Sciences Research Council (EPSRC) [Grant Numbers EP/J015180/1 and EP/K014227/1], and the MOD University Defence Research Collaboration (UDRC) in Signal Processing.
Venue - Dates:
27th AAS/AIAA Space Flight Mechanics Meeting, 2017, , San Antonio, United States, 2017-02-05 - 2017-02-09
Identifiers
Local EPrints ID: 475503
URI: http://eprints.soton.ac.uk/id/eprint/475503
ISSN: 0065-3438
PURE UUID: 5425080f-ace6-4c3e-8885-a550b7760c4e
Catalogue record
Date deposited: 20 Mar 2023 17:46
Last modified: 17 Mar 2024 13:11
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Contributors
Author:
E. D. Delande
Author:
J. Houssineau
Author:
J. Franco
Author:
C. Frueh
Author:
D. E. Clark
Editor:
Jon A. Sims
Editor:
Frederick A. Leve
Editor:
Jay W. McMahon
Editor:
Yanping Guo
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