Next Article in Journal
Analysis of Radio Wave Propagation for ISM 2.4 GHz Wireless Sensor Networks in Inhomogeneous Vegetation Environments
Previous Article in Journal
On the Potential Usefulness of Fourier Spectra of Delayed Fluorescence from Plants
Article Menu

Export Article

Open AccessArticle
Sensors 2014, 14(12), 23630-23649; doi:10.3390/s141223630

Performance Enhancement for a GPS Vector-Tracking Loop Utilizing an Adaptive Iterated Extended Kalman Filter

1,2,* , 1,2
and
3
1
School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China
2
Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology Ministry of Education, Southeast University, Nanjing 210096, China
3
School of Automation and Electrical Engineering, University of Jinan, Jinan 250022, China
*
Author to whom correspondence should be addressed.
Received: 6 August 2014 / Revised: 27 October 2014 / Accepted: 3 December 2014 / Published: 9 December 2014
(This article belongs to the Section Remote Sensors)
View Full-Text   |   Download PDF [1983 KB, uploaded 9 December 2014]   |  

Abstract

This paper deals with the problem of state estimation for the vector-tracking loop of a software-defined Global Positioning System (GPS) receiver. For a nonlinear system that has the model error and white Gaussian noise, a noise statistics estimator is used to estimate the model error, and based on this, a modified iterated extended Kalman filter (IEKF) named adaptive iterated Kalman filter (AIEKF) is proposed. A vector-tracking GPS receiver utilizing AIEKF is implemented to evaluate the performance of the proposed method. Through road tests, it is shown that the proposed method has an obvious accuracy advantage over the IEKF and Adaptive Extended Kalman filter (AEKF) in position determination. The results show that the proposed method is effective to reduce the root-mean-square error (RMSE) of position (including longitude, latitude and altitude). Comparing with EKF, the position RMSE values of AIEKF are reduced by about 45.1%, 40.9% and 54.6% in the east, north and up directions, respectively. Comparing with IEKF, the position RMSE values of AIEKF are reduced by about 25.7%, 19.3% and 35.7% in the east, north and up directions, respectively. Compared with AEKF, the position RMSE values of AIEKF are reduced by about 21.6%, 15.5% and 30.7% in the east, north and up directions, respectively. View Full-Text
Keywords: Global Positioning System (GPS); iterated extended Kalman filter (IEKF); model error; nonlinear filtering; vector-tracking Global Positioning System (GPS); iterated extended Kalman filter (IEKF); model error; nonlinear filtering; vector-tracking
Figures

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Chen, X.; Wang, X.; Xu, Y. Performance Enhancement for a GPS Vector-Tracking Loop Utilizing an Adaptive Iterated Extended Kalman Filter. Sensors 2014, 14, 23630-23649.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top