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Industrial IoT Technologies and Applications. 4th EAI International Conference, Industrial IoT 2020, Virtual Event, December 11, 2020, Proceedings

Research Article

Beyond Anchors: Optimal Equality Constraints in Cooperative Localization

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  • @INPROCEEDINGS{10.1007/978-3-030-71061-3_4,
        author={Ping Zhang and Fei Cheng and Jian Lu},
        title={Beyond Anchors: Optimal Equality Constraints in Cooperative Localization},
        proceedings={Industrial IoT Technologies and Applications. 4th EAI International Conference, Industrial IoT 2020, Virtual Event, December 11, 2020, Proceedings},
        proceedings_a={INDUSTRIALIOT},
        year={2021},
        month={7},
        keywords={Cram\^{e}r-Rao Lower Bound (CRLB) Equality constraints Maximum Likelihood Estimate (MLE) Singular Value Decomposition (SVD) Wireless Sensor Networks (WSN)},
        doi={10.1007/978-3-030-71061-3_4}
    }
    
  • Ping Zhang
    Fei Cheng
    Jian Lu
    Year: 2021
    Beyond Anchors: Optimal Equality Constraints in Cooperative Localization
    INDUSTRIALIOT
    Springer
    DOI: 10.1007/978-3-030-71061-3_4
Ping Zhang1, Fei Cheng1, Jian Lu1
  • 1: Anhui Polytechnic University

Abstract

Although anchors are the most common in cooperative localizations, they are not the optimal in the class of equality constraints which provide the global reference information for deriving absolute locations. Using Cramér-Rao lower bound (CRLB) to evaluate the localization accuracy, this paper derives the optimal equality constraints that achieve the lowest CRLB trace under given constraint number, and analyzes the feasibility of constructing the optimal constraints before knowing the node ground truth locations. Simulations compare the performance between the anchor-type constraints and the optimal ones, and suggest a cooperative localization algorithm by using the optimal equality constraints.

Keywords
Cramér-Rao Lower Bound (CRLB) Equality constraints Maximum Likelihood Estimate (MLE) Singular Value Decomposition (SVD) Wireless Sensor Networks (WSN)
Published
2021-07-16
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-030-71061-3_4
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