Multipath estimation using an intelligent optimization algorithm with non-Gaussian noise

Cheng, Lan and Yue, Hong and Xie, Gang and Ren, Mifeng; (2017) Multipath estimation using an intelligent optimization algorithm with non-Gaussian noise. In: The 23rd International Conference on Automation and Computing (ICAC'17). IEEE, GBR.

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Abstract

Multipath is known to be one of the dominant error sources in high accuracy positioning systems, and multipath estimation is crucial for multipath mitigation. Most existing multipath estimation algorithms usually consider the cases of single mutlipath with Gaussian noise. However, non-Gaussian noises and two - multipath are often encountered in many practical environments. In this paper, a new algorithm is proposed to cope with the multipath estimation problem of the latter. First, the multipath estimation problem is transferred into a constrained optimization problem using the central error entropy criterion (CEEC) as its objective function. The second-order moment of the estimation error and the prior information are taken as constraints to reduce the mean of the estimation error. Then, a modified ε-constrained rank-based differential evolution (εRDE) algorithm is explored to solve the optimization problem. The proposed algorithm has been compared with the particle filter algorithm using a two-multipath case study example with non-Gaussian noises. The results suggest the proposed algorithm has improved the multipath estimation accuracy.

ORCID iDs

Cheng, Lan, Yue, Hong ORCID logoORCID: https://orcid.org/0000-0003-2072-6223, Xie, Gang and Ren, Mifeng;
  • Item type:Book Section
    ID code:61746
    Dates:
    Date
    Event
    26 October 2017
    Published
    14 June 2017
    Accepted
    Notes:(c) 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
    Subjects:Technology > Electrical engineering. Electronics Nuclear engineering
    Department:Faculty of Engineering > Electronic and Electrical Engineering
    Depositing user: Pure Administrator
    Date deposited:06 Sep 2017 15:33
    Last modified:11 Nov 2024 15:11
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/61746
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