Delande, E., Houssineau, Jeremie, Franco, J., Frueh, C., Clark, D. and Jah , M. (2019) A new multi-target tracking algorithm for a large number of orbiting objects. Advances in Space Research . doi:10.1016/j.asr.2019.04.012 (In Press)

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Abstract

This paper presents the filter for Hypothesised and Independent Stochastic Populations (HISP), a multi-object joint detection/tracking algorithm derived from a recent estimation framework for stochastic populations, in the context of Space Situational Awareness. Designed for multi-object estimation problems where the data association between tracks and collected observations is moderately ambiguous, the HISP filter has a linear complexity with the number of objects and the number of observations. Because of its scalable complexity, the HISP filter is a promising solution for the construction of a large-scale catalogue of Resident Space Objects. We illustrate the HISP filter on a challenging surveillance scenario built from real data for 115 satellites of PlanetLabs’ Dove constellation, and simulated observations collected from two sensors with limited coverage and measurement noise, in the presence of false positives and missed detection.

Item Type:	Journal Article
Divisions:	Faculty of Science > Statistics
Journal or Publication Title:	Advances in Space Research
Publisher:	Elsevier Science BV
ISSN:	0273-1177
Official Date:	13 May 2019
Dates:	Date Event 13 May 2019 Available 10 April 2019 Accepted
DOI:	10.1016/j.asr.2019.04.012
Status:	Peer Reviewed
Publication Status:	In Press
Access rights to Published version:	Restricted or Subscription Access
Related URLs:	Publisher

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