This article is dedicated to the estimation of the GNSS signal carrier-to-noise ratio using the in-phase component of the signals as observations. In a GNSS receiver, it is the statistic of the correlation provided by the code tracking loop that is used to estimate the carrier-to-noise ratio. In fact, carrier-to-noise estimation is used to monitor the performance of GNSS receivers and the quality of the received signals. In this article, we aim at high rate carrier-to-noise estimation, namely the code repetition rate (e.g. 1ms for GPS C/A), in order to maximize the time resolution of carrier-to-noise observations. We show that in a 1-bit quantization receiver, the in-phase component of the signal can provide a direct observation of the signal amplitude, and therefore of the carrier-to-noise ratio. However, the model that links the 1ms rate observations of the in-phase component with the signal amplitude is non-linear. The non-linear expression that links the maximum value of the in-phase correlation component to the signal amplitude is derived. In order to estimate the time varying amplitudes of the signals, we propose an Extended Kalman Filter to reverse the non-linear expression with the noisy observations of correlation provided by the tracking loop. The proposed model and filter inversion method are assessed on synthetic and real data, while investigating the effect of the cross-correlation contribution of the visible satellites on the estimations. We show using real data that, for a 1-bit quantization receiver, the proposed estimator can achieve the same accuracy as a widely known commercial GNSS receiver with a much higher data rate. We also show that the proposed approach can cope with abrupt changes in the observations compared to a classical $C/N_0$ estimate.

本文致力于使用信号的同相分量作为观测值来估算GNSS信号的载噪比。在GNSS接收机中，由代码跟踪环路提供的相关性统计信息可用于估算载波噪声比。实际上，载波噪声估计用于监视GNSS接收机的性能和接收信号的质量。在本文中，我们旨在实现高速率的信噪比估计，即码重复率（例如，GPS C / A为1毫秒），以便最大化信噪比观测的时间分辨率。我们表明，在1位量化接收机中，信号的同相分量可以直接观察信号幅度，从而可以直接观察到载波噪声比。然而，将同相分量的1ms速率观测值与信号幅度联系起来的模型是非线性的。得出将同相相关分量的最大值与信号幅度联系起来的非线性表达式。为了估计信号随时间变化的幅度，我们提出了一个扩展卡尔曼滤波器，利用跟踪环路提供的相关噪声观测来逆转非线性表达式。在研究合成卫星和真实数据的基础上，对提出的模型和滤波器反演方法进行了评估，同时研究了可见卫星互相关贡献对估计的影响。我们显示，使用实际数据可以看到，对于1位量化接收器，所提出的估计器可以达到与广为人知的商用GNSS接收器相同的精度，但数据速率要高得多。$C/{ñ}_0$ 估计。