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Session B4: Spectrum: Protection and Optimization

Enhancement and Extensions to a Cyclostationary GNSS Self-Interference Model
Christopher Hegarty, Brady O'Hanlon, The MITRE Corporation
Date/Time: Thursday, Sep. 19, 4:46 p.m.

In prior work, a simple method was derived for predicting the impact of GPS C/A-code self-interference on receiver functions that are dependent solely on prompt 20-ms correlation sums (e.g., carrier phase tracking, and data demodulation). The method models the GPS C/A-code signal as a cyclostationary random process, treating each GPS C/A signal’s pseudorandom noise (PRN) code as a random 1023-bit sequence that repeats twenty times every 20-ms navigation data bit. A two-parameter autocorrelation function is then used to obtain a simple equation for the level of additive white Gaussian noise (AWGN) that produces the same receiver effects as the C/A-code self-interference. The method has been demonstrated to be significantly more accurate in predicting GPS C/A-code self-interference than prior models.

In this paper, an enhancement and extensions to the C/A-code self-interference method are derived and evaluated. The enhancement is the replacement of the random model for each C/A-code PRN with the use of the true codes. Using the true PRN codes is more complicated but is shown to result in slightly more accurate results in certain conditions. The extensions are adaptions of the C/A-code self-interference method to additional GNSS signal pairs. For instance, the method has been adapted to examine interactions between the GPS C/A-code signal and the C/B signal utilized by Japan’s Quasi-Zenith Satellite System (QZSS). The C/B signal utilizes length-1023 Gold codes from the same family as the GPS C/A-code signals but additionally employs a 1.023 MHz square wave component. The C/A-code self-interference method has also been extended to examine the interference from non-standard GPS C/A signals to normal GPS C/A signals. This paper provides both derivations of new theoretical results and validation of select results through Monte Carlo receiver simulations.

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