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Impact of Decorrelation on Success Rate Bounds of Ambiguity Estimation

Published online by Cambridge University Press:  28 March 2016

Lei Wang ,
Yanming Feng ,
Jiming Guo  and
Charles Wang
Lei Wang*
Affiliation:
(Queensland University of Technology, Brisbane, Australia) (School of Geodesy and Geomatics, Wuhan University, China)
Yanming Feng
Affiliation:
(Queensland University of Technology, Brisbane, Australia)
Jiming Guo
Affiliation:
(School of Geodesy and Geomatics, Wuhan University, China)
Charles Wang
Affiliation:
(Queensland University of Technology, Brisbane, Australia)
*
(E-mail: [email protected])
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Abstract

Reliability is an important performance measure of navigation systems and this is particularly true in Global Navigation Satellite Systems (GNSS). GNSS positioning techniques can achieve centimetre-level accuracy which is promising in navigation applications, but can suffer from the risk of failure in ambiguity resolution. Success rate is used to measure the reliability of ambiguity resolution and is also critical in integrity monitoring, but it is not always easy to calculate. Alternatively, success rate bounds serve as more practical ways to assess the ambiguity resolution reliability. Meanwhile, a transformation procedure called decorrelation has been widely used to accelerate ambiguity estimations. In this study, the methodologies of bounding integer estimation success rates and the effect of decorrelation on these success rate bounds are examined based on simulation. Numerical results indicate decorrelation can make most success rate bounds tighter, but some bounds are invariant or have their performance degraded after decorrelation. This study gives a better understanding of success rate bounds and helps to incorporate decorrelation procedures in success rate bounding calculations.

Keywords

ReliabilityAmbiguity EstimationSuccess RateDecorrelation
Type
Research Article
Information
The Journal of Navigation , Volume 69 , Issue 5 , September 2016 , pp. 1061 - 1081
Copyright
Copyright © The Royal Institute of Navigation 2016 

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