The IFFT-based SQM method against digital distortion in GNSS signals

Global navigation satellite systems (GNSS) signal deformations could threaten the position accuracy and integrity of GNSS, especially for safety critical applications. Digital distortion is an important kind of deformations caused by failures inside the baseband generation unit onboard the GNSS satellites. Multi-correlator technique, as a prevalent signal quality monitoring (SQM) method, was developed to reliably detect the signal anomaly and therefore protect airborne users from this integrity threat. However, the conventional multi-correlator technique is unable to estimate the degree of distortion quantitatively, while another SQM method, the chip domain observable, has a poor real-time capability so that it could not meet the stringent time to alarm requirements. To solve the above problem, we derived the spectrum form of the conventional Threat Model A first and proposed a IFFT-based SQM algorithm. This new method can perform SQM easily by analyzing the impulses after PSD division and IFFT: Detect the presence of digital distortion by judging whether there is an impulse after IFFT and estimate the degree of distortion by computing the offset of the impulse. The results show that the IFFT-based method can not only detect digital distortion real-timely but also estimate the digital distortion degree quantitatively.

[1]  A.J. Van Dierendonck,et al.  Recommendations on digital distortion requirements for the civil GPS signals , 2008, 2008 IEEE/ION Position, Location and Navigation Symposium.

[2]  Patrick C. Fenton,et al.  The Theory and Performance of NovAtel Inc.'s Vision Correlator , 2005 .

[3]  Wenquan Feng,et al.  A Novel Digital Threat Model and Effect Analysis on Modernized BeiDou Signals , 2016 .

[4]  A. Jakab,et al.  An Approach to GPS Satellite Failure Detection , 1999 .

[5]  M. Raimondi,et al.  Generating Evil WaveForms on Galileo signals using NAVYS , 2012, 2012 6th ESA Workshop on Satellite Navigation Technologies (Navitec 2012) & European Workshop on GNSS Signals and Signal Processing.

[6]  Johann Furthner,et al.  GIOVE-A initial signal analysis , 2006 .

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

[8]  Dennis M. Akos,et al.  A Real-Time Signal Quality Monitor For GPS Augmentation Systems , 2000 .

[9]  Michael Meurer,et al.  A multi-technique approach for characterizing the SVN49 signal anomaly, part 2: chip shape analysis , 2011, GPS Solutions.

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

[11]  Michael Meurer,et al.  Characterization of Nominal Signal Distortions and Impact on Receiver Performance for GPS (IIF) L1/L5 and Galileo (IOV) E1 /E5a Signals , 2014 .

[12]  Oliver Montenbruck,et al.  Potentials for GNSS Signal Enhancements –An Assessment of the Impact of Satellite Imperfections on the Navigation Performance of Today’s and Future GNSS , 2010 .

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

[14]  Olivier Julien,et al.  Estimation of GNSS Signals’ Nominal Distortions from Correlation and Chip Domain , 2015 .

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

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

[17]  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.