Maximum Likelihood Code Phase Discriminator for GNSS

Rabih Chrabieh, Nathan Arbeid

Abstract: Abstract—We present a Maximum Likelihood code phase discriminator for GNSS. In the absence of overlapping multipath, it optimizes the interpolation of a few correlators to locate the peak of the correlation, i.e., the time of arrival of the signal. A key point is that noise whitening is applied post-correlation. We show how it outperforms classical code phase discriminators in terms of converging to an accurate TOA, for both the coherent and non-coherent cases, at high or low SNR. For the noncoherent correlators, we show the benefit of computing the correlators covariance matrix. The discriminator can use any set of correlators having any spacings, and it can account for time drifting correlators and for PRN auto-correlation distortions. A benefit is improved responsiveness to satellite tracking in difficult environments. Faster convergence to the solution enables efficient software implementations and reduced power consumption. The ML discriminator is particularly suitable for computationally intensive wide band systems such as GPS L5, or for terrestrial beacon systems such as TerraPoiNT, 4G or 5G. Index Terms—GNSS, code phase discriminator, delay locked loop, maximum likelihood
Published in: 2023 IEEE/ION Position, Location and Navigation Symposium (PLANS)
April 24 - 27, 2023
Hyatt Regency Hotel
Monterey, CA
Pages: 977 - 986
Cite this article: Chrabieh, Rabih, Arbeid, Nathan, "Maximum Likelihood Code Phase Discriminator for GNSS," 2023 IEEE/ION Position, Location and Navigation Symposium (PLANS), Monterey, CA, April 2023, pp. 977-986.
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