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Sensors 2018, 18(9), 3005;

Distributed Space Debris Tracking with Consensus Labeled Random Finite Set Filtering

School of Mechanical and Electric Engineering, Guangzhou University, Guangzhou 510006, China
School of Electrical, Electronic, and Computer Engineering, the University of Western Australia, Crawley, WA 6009, Australia
This paper is an extended version of the conference paper: Baishen, W.; Brett, N. Consensus labeled multi-Bernoulli filtering for distributed space debris tracking. In Proceedings of the 2017 International Conference on Control, Automation and Information Sciences (ICCAIS), Chiang Mai, Thailand, 31 October–1 November 2017.
Author to whom correspondence should be addressed.
Received: 25 July 2018 / Revised: 3 September 2018 / Accepted: 5 September 2018 / Published: 7 September 2018
(This article belongs to the Special Issue Multiple Object Tracking: Making Sense of the Sensors)
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Space debris tracking is a challenge for spacecraft operation because of the increasing number of both satellites and the amount of space debris. This paper investigates space debris tracking using marginalized δ -generalized labeled multi-Bernoulli filtering on a network of nodes consisting of a collection of sensors with different observation volumes. A consensus algorithm is used to achieve the global average by iterative regional averages. The sensor network can have unknown or time-varying topology. The proposed space debris tracking algorithm provides an efficient solution to the key challenges (e.g., detection uncertainty, data association uncertainty, clutter, etc.) for space situational awareness. The performance of the proposed algorithm is verified by simulation results. View Full-Text
Keywords: space debris; marginalized δ-GLMB; distributed; consensus space debris; marginalized δ-GLMB; distributed; consensus

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Wei, B.; Nener, B. Distributed Space Debris Tracking with Consensus Labeled Random Finite Set Filtering. Sensors 2018, 18, 3005.

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