1. bookVolume 18 (2017): Issue 2 (June 2017)
Journal Details
License
Format
Journal
First Published
20 Mar 2000
Publication timeframe
4 times per year
Languages
English
access type Open Access

GNSS Positioning Performance Analysis Using PSO-RBF Estimation Model

Published Online: 26 Apr 2017
Page range: 146 - 154
Journal Details
License
Format
Journal
First Published
20 Mar 2000
Publication timeframe
4 times per year
Languages
English

Positioning solutions need to be more precise and available. The most frequent method used nowadays includes a GPS receiver, sometimes supported by other sensors. Generally, GPS and GNSS suffer from spreading perturbations that produce biases on pseudo-range measurements. With a view to optimize the use of the satellites received, we offer a positioning algorithm with pseudo range error modelling with the contribution of an appropriate filtering process. Extended Kalman Filter, The Rao- Blackwellized filter are among the most widely used algorithms to predict errors and to filter the high frequency noise. This paper describes a new method of estimating the pseudo-range errors based on the PSO-RBF model which achieves an optimal training criterion. This model is appropriate of its method to predict the GPS corrections for accurate positioning, it reduce the positioning errors at high velocities by more than 50% compared to the RLS or EKF methods.

Keywords

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