Paper
19 April 2011 The improvement of accuracy of standalone GPS with an alternative positioning algorithm
Author Affiliations +
Abstract
Commercial standalone Global Positioning System (GPS) receivers suffer from multiple errors including multipath bias and ionospheric signal disturbance, especially in urban environment where GPS signal can be easily affected and altered. There are multiple techniques to solve this issue, yet every method has limitations and certain problems. Furthermore, the positioning accuracy of the commercial low-cost GPS is very poor in urban conditions, in most cases due to multi-path bias. In this paper, a novel method was proposed which introduced certain parameters and weighted coefficients to the existing GPS positioning algorithm in order to compensate the impact of multi-path and poor signal receptions. The measurement accuracy of the commercial GPS receiver with existing algorithms and that of the new algorithm proposed have been studied simultaneously to determine the improvement. Tests performed in Boston metropolitan area, using low-cost off-the-shelf equipment, show that the new method yields over 50% accuracy improvements (RMS) and fewer fluctuations than conventional algorithms implemented. These studies demonstrated that better accuracy could be achieved by considering the relationship between multi-path bias and signal strength. The detailed analysis of applying different parameters in various conditions with experiment results is presented in the paper.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jiaxing Zhang, Yi Zhang, and Ming Wang "The improvement of accuracy of standalone GPS with an alternative positioning algorithm", Proc. SPIE 7983, Nondestructive Characterization for Composite Materials, Aerospace Engineering, Civil Infrastructure, and Homeland Security 2011, 79832T (19 April 2011); https://doi.org/10.1117/12.880678
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KEYWORDS
Satellites

Global Positioning System

Receivers

Signal to noise ratio

Stochastic processes

Clocks

Copper

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