International Global Navigation Satellite Systems Association
IGNSS Conference 2016
Colombo Theatres, Kensington Campus, UNSW Australia
6 – 8 December 2016
Real-time Cycle Slip Detection and Repair for
Network Multi-GNSS, Multi-frequency data
processing
Tao Li (1)
Cooperative Research Centre for Spatial Information, Melbourne, Australia
Geoscience Australia, Canberra, Australia
+61 (2) 6249 9510 Tao.Li@ga.gov.au
Stavros Melachroinos (2)
Geoscience Australia, Canberra, Australia
+61 (2) 6249 9479 Stavros.Melachroinos@ga.gov.au
ABSTRACT
The GNSS community is experiencing a new era with the development of
the multi-GNSS and multi-frequency industry. For high-precision GNSS
data processing with the use of carrier phase measurements, quality control
steps, such as, cycle slip detection and repair, are essential. With the correct
detection and repair of the cycle slips, the carrier phase measurements will
not be lumped by the unknown integer jumps. Therefore repeated integer
ambiguity resolution in RTK or long convergence time in PPP, or PPP-RTK,
will be avoided, especially in the extreme case of full loss of all the signals.
In this contribution, a cycle slip detection and repair procedure, which has
been implemented into our real-time Analysis Centre Software (ACS) pre-
processing and data editing (PDE) function, is presented. At first, the noise
levels of Hatch-Melbourne-Wübbena (MW) and Extra MW (EMW) linear
combinations are investigated. The cycle slip detection approaches based on
linear combinations and quality control theory under statistical hypothesis
testing are then comparatively studied with multi-GNSS and multi-frequency
data. As soon as the cycle slips are detected, mathematical and stochastic
models for cycle slip repair are established. These models rely on time-
differenced code and carrier phase measurements, as well as prior
knowledge of the time-differenced ionosphere residual. The least-squares
estimation is used to estimate the unknown parameters and their variance-
covariance matrix. The float cycle slips and their variance covariance matrix
are then used to reliably repair the cycle slips based on Integer Least-squares
(ILS) estimation. Overall, the numerical results indicate the effectiveness of
the implemented method for real-time network multi-GNSS and multi-
frequency data processing. Moreover, the benefits of the triple-frequency
cycle slip detection and repair algorithm are demonstrated.
KEYWORDS: GNSS; Cycle Slip; Detection, Repair; Triple-Frequency
