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

Lan Cheng, Hong Yue, Gang Xie, Mifeng Ren

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

2 Citations (Scopus)

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.
LanguageEnglish
Title of host publicationThe 23rd International Conference on Automation and Computing (ICAC'17)
Place of PublicationPiscaaway, N.J.
PublisherIEEE
Number of pages6
Publication statusPublished - 26 Oct 2017
EventThe 23rd International Conference on Automation and Computing - University of Huddersfield, Huddersfield, United Kingdom
Duration: 7 Sep 20178 Sep 2017
http://www.cacsuk.co.uk/index.php/conferences

Conference

ConferenceThe 23rd International Conference on Automation and Computing
Abbreviated titleICAC'17
CountryUnited Kingdom
CityHuddersfield
Period7/09/178/09/17
Internet address

Fingerprint

Error analysis
Constrained optimization
Entropy

Keywords

  • multipath estimation
  • optimization
  • entral error entropy criterion
  • non-Gaussian noise

Cite this

Cheng, L., Yue, H., Xie, G., & Ren, M. (2017). Multipath estimation using an intelligent optimization algorithm with non-Gaussian noise. In The 23rd International Conference on Automation and Computing (ICAC'17) Piscaaway, N.J.: IEEE.
Cheng, Lan ; Yue, Hong ; Xie, Gang ; Ren, Mifeng. / Multipath estimation using an intelligent optimization algorithm with non-Gaussian noise. The 23rd International Conference on Automation and Computing (ICAC'17). Piscaaway, N.J. : IEEE, 2017.
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author = "Lan Cheng and Hong Yue and Gang Xie and Mifeng Ren",
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Cheng, L, Yue, H, Xie, G & Ren, M 2017, Multipath estimation using an intelligent optimization algorithm with non-Gaussian noise. in The 23rd International Conference on Automation and Computing (ICAC'17). IEEE, Piscaaway, N.J., The 23rd International Conference on Automation and Computing , Huddersfield, United Kingdom, 7/09/17.

Multipath estimation using an intelligent optimization algorithm with non-Gaussian noise. / Cheng, Lan; Yue, Hong; Xie, Gang; Ren, Mifeng.

The 23rd International Conference on Automation and Computing (ICAC'17). Piscaaway, N.J. : IEEE, 2017.

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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N1 - (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.

PY - 2017/10/26

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N2 - 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.

AB - 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.

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Cheng L, Yue H, Xie G, Ren M. Multipath estimation using an intelligent optimization algorithm with non-Gaussian noise. In The 23rd International Conference on Automation and Computing (ICAC'17). Piscaaway, N.J.: IEEE. 2017