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A Review of Robust Cost Functions for M-Estimation

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Communications, Signal Processing, and Systems (CSPS 2020)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 654))

Abstract

Robust state estimation plays a key role in mobile robotic navigation, and the M-estimation technique can effectively handle outliers. In this paper, the commonly used robust cost functions for M-estimation are given, and their cost, influence, and weight functions are summarized and compared.

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Acknowledgements

This work was supported by the Pre-Research Project of Space Science (No. XDA15014700), the National Natural Science Foundation of China (No. 61601328), the Scientific Research Plan Project of the Committee of Education in Tianjin (No. JW1708), and the Doctor Foundation of Tianjin Normal University (No. 52XB1417).

Author information

Authors and Affiliations

  1. Key Laboratory of Electronics and Information Technology for Space Systems, Chinese Academy of Sciences, Beijing, 100190, China

    Yue Wang

  2. Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission, Tianjin Normal University, Tianjin, 300387, China

    Yue Wang

Authors
  1. Yue Wang
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Corresponding author

Correspondence to Yue Wang .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, University of Texas at Arlington, Arlington, TX, USA

    Qilian Liang

  2. Tianjin Normal University, Tianjin, China

    Wei Wang

  3. Dalian University of Technology, Dalian, China

    Xin Liu

  4. School of Information Science and Technology, Dalian Maritime University, Dalian, China

    Zhenyu Na

  5. Huazhong Agricultural University, Wuhan, China

    Xiaoxia Li

  6. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Baoju Zhang

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Wang, Y. (2021). A Review of Robust Cost Functions for M-Estimation. In: Liang, Q., Wang, W., Liu, X., Na, Z., Li, X., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2020. Lecture Notes in Electrical Engineering, vol 654. Springer, Singapore. https://doi.org/10.1007/978-981-15-8411-4_99

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  • DOI: https://doi.org/10.1007/978-981-15-8411-4_99

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-8410-7

  • Online ISBN: 978-981-15-8411-4

  • eBook Packages: EngineeringEngineering (R0)

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