Maximum Likelihood Code Phase Discriminator for GNSS

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 non-coherent 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.