Global tracking of space debris via CPHD and consensus

Baishen Wei, Brett Nener, Weifeng Liu, Liang Ma

    Research output: Contribution to journalArticle

    5 Citations (Scopus)

    Abstract

    Space debris tracking is of great importance for safe operation of spacecraft. This paper presents an algorithm that achieves global tracking of space debris with a multi-sensor network. The sensor network has unknown and possibly time-varying topology. A consensus algorithm is used to effectively counteract the effects of data incest. Gaussian Mixture-Cardinalized Probability Hypothesis Density (GM-CPHD) filtering is used to estimate the state of the space debris. As an example of the method, 45 clusters of sensors are used to achieve global tracking. The performance of the proposed approach is demonstrated by simulation experiments.

    Original languageEnglish
    Pages (from-to)2548-2562
    Number of pages15
    JournalAdvances in Space Research
    Volume59
    Issue number10
    DOIs
    Publication statusPublished - 10 Mar 2017

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