An experimental implementation of a particle-based dynamic sensor steering method for tracking and searching for space objects

Hobson, Tyler A. and Clarkson, I. Vaughan L. (2014). An experimental implementation of a particle-based dynamic sensor steering method for tracking and searching for space objects. In: Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on. 2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014, Florence, Italy, (8018-8022). 4-9 May 2014. doi:10.1109/ICASSP.2014.6855162

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Author Hobson, Tyler A.
Clarkson, I. Vaughan L.
Title of paper An experimental implementation of a particle-based dynamic sensor steering method for tracking and searching for space objects
Conference name 2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014
Conference location Florence, Italy
Conference dates 4-9 May 2014
Convener IEEE
Proceedings title Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on   Check publisher's open access policy
Journal name IEEE International Conference on Acoustics, Speech and Signal Processing. Proceedings   Check publisher's open access policy
Series IEEE International Conference on Acoustics, Speech and Signal Processing. Proceedings
Place of Publication Piscataway, NJ United States
Publisher Institute of Electrical and Electronics Engineers
Publication Year 2014
Year available 2014
Sub-type Fully published paper
DOI 10.1109/ICASSP.2014.6855162
Open Access Status
ISBN 9781479928927
ISSN 1520-6149
Start page 8018
End page 8022
Total pages 5
Collection year 2015
Language eng
Abstract/Summary We present practical, experimental results for a system, driven by a particle filter, that dynamically steers a space surveillance sensor to track and search for resident space objects. In contrast to traditional Kalman-filter-based trackers, this system can exploit scheduled observations where the target is not found within the field of view. Furthermore, real-time observation-evaluation enables the system to immediately respond to these events by conducting a limited search. We describe the system and report the results of a recent field trial using a computer-controlled Raven-class electro-optical sensor to track objects using two-line element sets (TLEs) of various ages. Even for quite old TLEs - in some cases over six months old - the system demonstrates successful, automatic reacquisition.
Keyword Intelligent sensors
Particle filters
Space Situational Awareness
Q-Index Code E1
Q-Index Status Confirmed Code
Institutional Status UQ

 
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