Analysing the ML-Based Algorithms for GNSS Data Bit Synchronization and Decoding

Abstract

The position, velocity, and time global navigation satellite systems are vulnerable to signal interference, distortion, jamming, and multipath, which could potentially render the entire system inoperable due to the generally weak signal strength in these conditions. Due to these problems, the Global Navigation Satellite Systems receiver is rendered inoperable by an exceptionally strong navigation frequency band signal along the satellite path. Since global navigation satellite systems are currently widely used, there is a significant increase in the risks of interference, distortion, and jamming. Multipath concerns have been the subject of extensive research with a variety of approaches. But, first, the level of the Global Navigation Satellite Systems multipath must be estimated using a sample of the total signal that the navigation space satellite emits. The satellite constellation and environmental errors have a significant impact on the navigation system. The maximum likelihood estimation technique is presented in this paper along with an evaluation of its consistency and reliability when the Global Navigation Satellite Systems signal multipath is present. As this paper discusses, multipath signals can be numerically discriminated using maximum likelihood estimation techniques based on receiver measurements without the need for additional devices. The measurements and output data derived from the Global Navigation Satellite Systems receiver configuration parameters are used in the maximum likelihood estimation. It was found that the overall performance of the space data synchronization is determined by the number of data bit transitions rather than the total number of bits. An observed state-space representation, lower signal $C/N_0$, and greater Doppler frequency inaccuracy require more data bits for estimation and computation. It was also observed that, in the majority of cases, if not all of them, the bit evolution occurs with a probability equal to 60% upper. With $C/N_0$ in marginal power estimated to 20 dB-Hz without Doppler error, it is probably going to reach the 95%–100% range. If the Doppler error is less than 6 dB-Hz, the signal attenuation caused by the Doppler inaccuracy is insignificant, and the maximum tolerance of the Doppler inaccuracy is 30 dB-Hz.