Vectorial integer bootstrapping: flexible integer estimation with application to GNSS

In this contribution, we extend the principle of integer bootstrapping (IB) to a vectorial form (VIB). The mathematical definition of the class of VIB-estimators is introduced together with their pull-in regions and other properties such as probability bounds and success rate approximations. The vectorial formulation allows sequential block-by-block processing of the ambiguities based on a user-chosen partitioning. In this way, flexibility is created, where for specific choices of partitioning, tailored VIB-estimators can be designed. This wide range of possibilities is discussed, supported by numerical simulations and analytical examples. Further guidelines are provided, as well as the possible extension to other classes of estimators.

Impact of Decorrelation on Success Rate Bounds of Ambiguity Estimation

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.