Using dual-polarization GPS antenna with optimized adaptive neuro-fuzzy inference system to improve single point positioning accuracy in urban canyons

Rui Sun, Linxia Fu, Guanyu Wang, Qi Cheng, Li Ta Hsu, Washington Yotto Ochieng

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

This paper builds on the machine learning research to propose two new algorithms based on optimizing the Adaptive Neuro Fuzzy Inference System (ANFIS) with a dual-polarization antenna to predict pseudorange errors by considering multiple variables including the right-hand circular polarized (RHCP) signal strength, signal strength difference between the left-hand circular polarized (LHCP) and RHCP outputs, satellites’ elevation angle, and pseudorange residuals. The final antenna position is calculated following the application of the predicted pseudorange errors to correct for the effects of non-line-of-sight (NLOS) and multipath signal reception. The results show that the proposed algorithm results in a 30% improvement in the root mean square error (RMSE) in the 2D (horizontal) component for static applications when the training and testing data are collected at the same location. This corresponds to 13% to 20% when the testing data is from locations away from that of the training dataset.

Original languageEnglish
Pages (from-to)41-60
Number of pages20
JournalNavigation, Journal of the Institute of Navigation
Volume68
Issue number1
DOIs
Publication statusPublished - 1 Mar 2021

Keywords

  • ANFIS
  • dual-polarization antenna
  • firefly algorithm
  • genetic algorithm
  • GPS

ASJC Scopus subject areas

  • Aerospace Engineering
  • Electrical and Electronic Engineering

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