Advances in the miniaturization, computational capabilities, and cost reduction of semiconductor technology have made global navigation satellite systems (GNSSs) the favorite choice for positioning. Currently, positioning is a key factor for many essential tasks in our modern society and will become even more important with the advent of new concepts such as the Internet of Things (IoT), smart cities and autonomous driving. The extensive use of GNSSs in a wide range of applications has caused their migration from the professional segment to the mass-market segment in terms of both technology and performance. This presents new and more stringent requirements in terms of accuracy, robustness, ubiquity, and continuity for the original “open sky” GNSS design. GNSS technology has experienced an unprecedented evolution in the last decade, and it is expected to exponentially evolve in the next decade. This evolution is considered in this paper with the aim of providing a unified reference for current GNSS receiver technologies and solutions and its expected evolution in the next decade. We consider receiver concepts, antennae, RF front ends, digital signal processing, and positioning algorithms. The impacts on the different GNSS market segments and applications are also analyzed.

This paper deals with the problem of sequentially detecting statistical changes. In particular, the focus is on transient change detection, in which a probability minimizing optimal criterion is desirable. This is in contrast with the traditional minimization of the detection delay, proposed in quickest change detection problems. A finite moving average stopping time is proposed for the general transient change detection problem. The statistical performance of this stopping time is investigated and compared to other methods available in the literature. The proposed stopping time and theoretical findings are applied to quality monitoring, including reliability monitoring in industrial processes and signal quality monitoring in global navigation satellite systems. Numerical simulations are presented to assess the goodness of the presented theoretical results, and the performance of the considered stopping times. This will show the superiority of the proposed scheme.

Local threats such as radio frequency interference, multipath and spoofing have attracted the attention of many researchers in the past years thus leading to a myriad of contributions in the field of threat detection. Nevertheless, the current state of the art relies on classical detection techniques, which are not well suited for threat detection. In this paper, we take a leap forward by adopting the so-called quickest detection framework. This approach fits perfectly in critical applications where the aim is to detect the presence of local threats as soon as possible in order to improve the integrity of GNSS receivers.

The paper addresses the transient change detection (TCD) problem, assuming that the duration of change is finite. The TCD criterion minimizes the worst-case probability of missed detection among all tests with a prescribed worst-case probability of false alarm. We study the fixed sample size (FSS) test as a solution to the TCD problem. First, the operating characteristics of the FSS test have been established for arbitrary pre- and post-change distributions. Next, a numerical method of the sample (block) size optimization has been considered for three particular log-likelihood ratio distributions, i.e., Gaussian, $\chi ^{2}$ and exponential. Moreover, simple asymptotic equations for the optimal operating characteristics and block size have been proposed in the Gaussian case. Numerical results are provided to confirm the theoretical findings for the above-mentioned distributions. The accuracy and sharpness of the asymptotic analytical equation is analyzed in the Gaussian case. Finally, the FSS test is compared to the finite moving average (FMA) test obtained by optimizing the CUSUM-type test with respect to the TCD optimality criterion for the above-mentioned distributions. The application of the FSS and FMA tests to the radio-navigation integrity monitoring is also considered.

Global Navigation Satellite Systems (GNSSs) have become a ubiquitous tool for our modern society to carry out vital tasks such as transportation, civil engineering or precision agriculture. This breath has reached the realm of safety-critical applications such as time management of critical infrastructures or autonomous vehicles, in which GNSS is an essential tool nowadays. Unfortunately, current GNSS performance is not enough to fulfill the requirements of these professional and critical applications. For this reason, the FANTASTIC project was launched to boost the adoption of these applications. The project was funded by the European GNSS agency (GSA) in order to enhance the robustness and accuracy of GNSS in harsh environments. This paper presents the part related to the development of a weighting and exclusion function with a dual circularly polarized antenna. The idea is to reduce the effects of multipath by weighting and/or excluding those measurements affected by multipath. The observables and other metrics obtained from a dual polarized antenna will be exploited to define an exclusion threshold and to provide the weights. Real-world experiments will show the improvement in the positioning solution, using all available constellations, obtained with the developed technique.