Medium frequency (MF) R-Mode is a terrestrial positioning, navigation and timing system which implements the frequency division multiple access (FMDA) concept with 500 Hz bandwidth per transmitter. The underlying idea is to exploit the DGNSS correction broadcast service as means for navigation. Thus, the transmitted signal is composed by a 100 bit/s minimum shift keying (MSK) carrying data and two aiding carriers at Hz from the channel central frequency. The ranges are derived from the phase estimates of aiding carriers. Therefore, their signal quality needs to be evaluated. Due to the continuous nature of the signal and the presence of the nearby MSK (Figure 1), a measure of the true in-band signal quality is difficult to be obtained.

Assessing the quality of a received navigation signal is of fundamental importance to predict the navigation receiver performance. The signal to noise ratio (SNR) and the carrier to noise density () ratio indicators are often used for this purpose. Both indicators are also used to optimize the receiver algorithms, to monitor the healthiness of the transmitted signals and to improve the positioning estimators.

This paper presents a method to estimate the for MF R-Mode signals. We consider the particular case of using the discrete Fourier Transform (DFT) as base algorithm to estimate the signals’ within our MF R-Mode receiver. We describe the framework for R-Model signal processing, as well as the definition of a estimator used for MF R-Model signals. Monte Carlo simulation are performed to characterize the estimator performance. Additionally, in-field measurements are used to validate the approach. As visible in Figure 2, the measured ranging performance (gray-scale points) follows the theoretical lower bound of the performance which proves that the estimated is a good indicator to measure the received signal quality under optimal propagation condition.