A study on the dependency of GNSS pseudorange biases on correlator spacing

We provide a comprehensive overview of pseudorange biases and their dependency on receiver front-end bandwidth and correlator design. Differences in the chip shape distortions among GNSS satellites are the cause of individual pseudorange biases. The different biases must be corrected for in a number of applications, such as positioning with mixed signals or PPP with ambiguity resolution. Current state-of-the-art is to split the pseudorange bias into a receiver- and a satellite-dependent part. As soon as different receivers with different front-end bandwidths or correlator designs are involved, the satellite biases differ between the receivers and this separation is no longer practicable. A test with a special receiver firmware, which allows tracking a satellite with a range of different correlator spacings, has been conducted with live signals as well as a signal simulator. In addition, the variability of satellite biases is assessed through zero-baseline tests with different GNSS receivers using live satellite signals. The receivers are operated with different settings for multipath mitigation, and the changes in the satellite-dependent biases depending on the receivers’ configuration are observed.

[1]  Wlodzimierz W. Lewandowski,et al.  Sensitivity to the external temperature of some GPS time receivers , 1990 .

[2]  Baocheng Zhang,et al.  A Novel Un-differenced PPP-RTK Concept , 2011, Journal of Navigation.

[3]  R. E. Phelts.  Multicorrelator techniques for robust mitigation of threats to GPS signal quality , 2001 .

[4]  L. Lestarquit,et al.  Characterising the GNSS correlation function using a high gain antenna and long coherent integration—Application to signal quality monitoring , 2012, Proceedings of the 2012 IEEE/ION Position, Location and Navigation Symposium.

[5]  Hama,et al.  Estimation of total electron content using very long baseline interferometer , 1990 .

[6]  Alan Dodson,et al.  Towards PPP-RTK: Ambiguity resolution in real-time precise point positioning , 2011 .

[7]  Dennis M. Akos,et al.  Effects of Signal Deformations on Modernized GNSS Signals , 2006 .

[8]  Per K. Enge,et al.  Signal Deformations On Nominally Healthy GPS Satellites , 2004 .

[9]  Dennis M. Akos,et al.  Analysis of GNSS Signals as Observed via a High Gain Parabolic Antenna , 2005 .

[10]  Brian Barker,et al.  A Co-operative Anomaly Resolution on PRN-19 , 1999 .

[11]  F. Boon,et al.  Mitigating Short-Delay Multipath: a Promising New Technique , 2001 .

[12]  J.-P. Berthias,et al.  Integer Ambiguity Resolution on Undifferenced GPS Phase Measurements and Its Application to PPP and Satellite Precise Orbit Determination , 2007 .

[13]  Dennis M. Akos,et al.  Robust Signal Quality Monitoring and Detection of Evil Waveforms , 2000 .

[14]  Paul Collins,et al.  Precise Point Positioning with Ambiguity Resolution using the Decoupled Clock Model , 2008 .

[15]  Per Enge,et al.  Characterization of Signal Deformations for GPS and WAAS Satellites , 2010 .

[16]  Per Enge,et al.  Alternative Characterization of Analog Signal Deformation for GNSS-GPS Satellites , 2011 .

[17]  Jason Jones,et al.  Theory and Performance of the Pulse Aperture Correlator , 2004 .

[18]  James R. Clynch,et al.  Variability of GPS satellite differential group delay biases , 1991 .

[19]  Michael Meurer,et al.  A multi-technique approach for characterizing the SVN49 signal anomaly, part 1: receiver tracking and IQ constellation , 2011, GPS Solutions.

[20]  Blair Fonville,et al.  ACCOUNTING FOR TIMING BIASES BETWEEN GPS, MODERNIZED GPS, AND GALILEO SIGNALS , 2005 .

[21]  Per Enge,et al.  Signal Quality Monitoring: Test Results , 2000 .

[22]  E. Sardón,et al.  Estimation of total electron content using GPS data: How stable are the differential satellite and receiver instrumental biases? , 1997 .