Relative Multiple Space Object Tracking Using Intensity Filters
Multitarget intensity filters, such as the probability hypothesis density (PHD) filter and cardinalized probability hypothesis density (CPHD) filter have been recently proposed as a means to track multiple space objects from both ground-based and space-based platforms. In many applications, the CPHD is chosen over the PHD filter, as it has been claimed to offer significant improvements in the accuracy of both its cardinality estimates and state estimates. To that end, in this study, Gaussian mixture implementations of both the PHD and CPHD filters are developed to track the relative states of nearby space objects with respect to an inspector spacecraft using angles-only measurements. The performance of each solution is evaluated over several metrics, including cardinality error, optimal sub-pattern assignment distance, and execution speed.
K. A. Legrand and K. J. DeMars, "Relative Multiple Space Object Tracking Using Intensity Filters," Proceedings of the 18th International Conference on Information Fusion (2015, Washington, DC), pp. 1253-1261, Institute of Electrical and Electronics Engineers (IEEE), Sep 2015.
18th International Conference on Information Fusion (2015: Jul. 6-9, Washington, DC)
Mechanical and Aerospace Engineering
Keywords and Phrases
Bandpass filters; Information fusion; Space platforms, Cardinalities; Cardinality estimates; Execution speed; Gaussian mixtures; Intensity filter; Probability hypothesis density; Probability hypothesis density filter; State estimates, Probability density function
International Standard Book Number (ISBN)
Article - Conference proceedings
© 2015 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
01 Sep 2015