Abstract
The global navigation satellite systems (GNSS) carrier phase measurements form the basis of high-precision satellite positioning. These measurements are often accompanied by their code counterparts to enable one to compute single-epoch ambiguity-resolved positioning solutions. To avoid unwanted code modelling errors, such as code multipath, one may opt for a phase-only solution and take recourse to carrier phase measurements of two successive epochs. In this paper we study the ambiguity resolution performance of a dual-epoch phase-only model, upon which the unknown positioning parameters are assumed to be completely unlinked in time. With the aid of closed-form analytical results, it is investigated how ambiguity resolution performs when dealing with high-rate phase data. It is thereby shown that multi-GNSS integration makes near real-time centimetre-level phase-only positioning possible. Our analytical analysis is supported by means of numerical results.
Highlights
Introduction pte Keywords Global Navigation SatelliteSystems (GNSS), Carrier phase measurements, Integer Ambiguity Resolution (IAR), Ambiguity Dilution OfPrecision (ADOP), High-rate data ce Department of Infrastructure Engineering, The University of Melbourne, Melbourne, AustraliaSchool of Science, RMIT University, Melbourne, Australia, Locata Corporation, Canberra, Australia AcAUTHOR SUBMITTED MANUSCRIPT - MST-112101.R1cri pt ical expectation operator
By increasing the sampling period to 10 seconds (i.e. τ = 10 sec), the stated precision improves to several metres which is still way poorer than the sub-centimetre precision of the phase-only fixed solutions bi
In case of 1Hz Global Navigation Satellite Systems (GNSS) phase measurements, the ambiguity-float baseline precision is about tens of metres
Summary
Systems (GNSS), Carrier phase measurements, Integer Ambiguity Resolution (IAR), Ambiguity Dilution Of. Precision (ADOP), High-rate data ce Department of Infrastructure Engineering, The University of Melbourne, Melbourne, Australia. The capital Q is reserved for (co)variance matrices, with Qxy being the n × p covariance matrix of two random vectors x ∈ Rn and y ∈ Rp. Qxx indicates the variance matrix of x. The transpose of a matrix is shown by the superscript. To express closed-form analytical results in a compact manner, the Kronecker matrix product ⊗ is employed (Henderson et al, 1983).
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