Advancements in communication, manufacturing, and launch technologies have significantly accelerated the development of Low-Earth orbit (LEO) satellite communication constellations. Simultaneously, the rapid expansion of LEO satellite platforms presents new opportunities for navigation enhancements and substantial benefits for internet of things (IoT) applications. This survey highlights the latest advancements in the integrated communication and navigation (ICAN) technologies, emphasizing key research issues. Specifically, we discuss the motivation and feasibility of integrating communication and navigation on LEO satellite platforms, analyzing various LEO-based navigation paradigms while assessing their respective advantages and limitations. We further explore the mutual promotion of navigation and communication under the ICAN paradigm and discuss waveform design, analyzing the characteristics of different waveform design approaches. Finally, we highlight the unique challenges and identify open research topics within the ICAN framework for future exploration.

Recent advancements in spaceborne receiver technology have extended the application of Global Navigation Satellite System (GNSS)-based navigation systems to space missions. However, the actual availability and usability of GNSS signals in deep-space is still questionable, lacking experimental evidence. The Lunar GNSS Receiver Experiment (LuGRE) is a joint NASA-Italian Space Agency (ASI) payload aiming to showcase GNSS-based Positioning, Navigation and Timing (PNT) during its transfer orbit to the Moon. Operating without direct interface with on-board Guidance, Navigation & Control (GNC) subsystems, the LuGRE receiver requires alternative means of aiding to pursue precise Orbit Determination (OD) in the challenging space environment. This paper investigates a custom Trajectory-Aware EKF (TA-EKF) architecture that integrates aiding observations in the form of a pre-mission design of the LuGRE trajectory. Two alternative designs are presented, integrating aiding observations in the observation-domain and state-domain, respectively. The proposed architectures are evaluated by post-processing raw GNSS observables collected in a real-time Hardware-in-the-Loop (HIL) simulation with GNSS Radio Frequency (RF) signals. A comprehensive assessment leveraging Monte Carlo (MC) analyses characterizes the OD performance under aiding observation errors and mismodeling, comparing the TA-EKF models against a standalone Extended Kalman Filter (EKF) solution.

Bayesian navigation filters are broadly exploited in precise state estimation for kinematic applications such as vehicular positioning and navigation. Among these, Particle Filter (PF) has been shown as a valuable solution to support hybrid positioning algorithms such as sensor fusion to Global Navigation Satellite System (GNSS) and Cooperative Positioning (CP). Despite of an increased computational complexity w.r.t. conventional Kalman Filters (KFs), an effective weighting of the input measurements generally provides an improved accuracy of the output estimate. In the framework of the Differential GNSS (DGNSS) CP, this work presents an algorithm for the automated selection of the most appropriate error models for the tight-integration of non-stationary Differential GNSS (DGNSS) collaborative inter-agent distances. A model switching technique named Automated Adaptive Likelihood Switch (AALS) is proposed for a Cognitive Particle Filter (C-PF) architecture, based on the real-time approximation of the statistics of the inter-agent distances errors. The results achieved through realistic simulations demonstrated the effectiveness of the proposed solution in terms of error model selection. Therefore, an improvement of the position estimation accuracy was observed, since the cases in which DGNSS-CP would degrade performance due to possible mismodelling of the selected likelihood function are avoided.

A global Internet of Things is possible by embracing constellations of satellites acting as orbiting gateways in a Direct-to-Satellite IoT (DtS-IoT). By removing the dependency on ground gateways, DtS-IoT enables a direct service on the regions illuminated by the passing-by satellite. After an in-depth overview of relevant experiments and candidate technologies, we discover that specific configurations of the Long-Range (LoRa) network protocol specification are particularly appealing to realize the DtS-IoT vision. Specifically, we profit from the maximum clock drift permitted on LoRa devices to propose the sparse satellite constellations concept. This approach significantly reduces the in-orbit DtS-IoT infrastructure at the expense of latency anyway present in resource-constrained IoT networks. We then introduce a novel algorithm comprising specific heuristics to design quasi-optimal topologies for sparse IoT constellations. Obtained results show that LoRa-compatible DtS-IoT services can already be provided world-wide with 10% and 4% of the satellites required for a traditional dense constellation, in different configurations.

GNSS is widely used to provide positions in an absolute reference frame in Unmanned Aerial Vehicles (UAV) and Unmanned Ground Vehicles (UGV), where GNSS is merged with the information provided by other sensors. Even if the main goal of GNSS signal processing is the positioning, multifrequency signals are a rich source of information about the propagation environment surrounding the mobile vehicle. In urban and harsh environment, situational awareness is essential to tailor the operations and take proper countermeasure to harsh propagation conditions. Given this framework the present paper will describe the use of GNSS as signals of opportunity for the characterization of the operative environment by processing the GNSS observables through Machine Learning (ML) algorithms that can be used as efficient features extractors. The paper will present some case studies of operational scenarios for UGVs and for a static monitoring station, showing how through combining DSP techniques with both unsupervised and supervised ML algorithms (K-means classes, Support Vector Machines) it is possible to retrieve the information about the propagation scenario for multipath, interference and atmospheric limitations.

The combination of ubiquitous network infrastructure and the high density of powerful, interconnected mobile devices in urban areas is driving the rise of smart cities. In parallel, the availability of ultra-low cost embedded Global Navigation Satellite System (GNSS) has enabled several affordable Location Based Services (LBS). New chipsets supporting dual frequency and multi- constellation GNSS signals are reducing the gap between high grade and mass market device performances. Among these devices, Android smartphones represent valuable and affordable tools for many LBS in the early advent of Intelligent Transportation Systems and smart vehicular navigation. Mobile networks natively provide a multiplicity of connected devices, thus enabling a family of applications demanding for a communication channel among GNSS receivers. This paper experimentally validates a collaborative technique based on the exchange of raw GNSS measurements to retrieve the relative range between Android smartphones. Additionally, a framework for the exchange of data between smartphones is provided, allowing the application of such a computationally-efficient ranging methodology in a network of low cost mobile devices within a smart city framework.

In the last decades, several positioning and navigation algorithms have been developed to enhance vehicular localization capabilities. Thanks to ad-hoc communication networks, the exchange of navigation data and positioning solutions has been exploited to the purpose. This trend has recently suggested the extension of state-of-the art navigation algorithms to the hybridization of independent heterogeneous measurements within collaborative frameworks. In this paper an integration paradigm based on the combination of Global Navigation Satellite System (GNSS) observable measurements is analysed. In this work, a comparison among legacy Extended Kalman Filter (EKF) and a suboptimal Particle Filter (s-PF) is proposed. First we show that under the same assumptions in non-collaborative framework the s-PF easily overcome EKF performances at the cost of a higher computational cost. On the contrary, by analysing a realistic scenario in which a target agent is aided by a set of collaborating peers we showed that a hybridized EKF implementation allows reaching and overcome PF performance at the only expense of network connectivity among few GNSS receivers, while the proposed integration induces minor benefits for an efficient s-PF.

This letter addresses the design and implementation of a monitoring station for Global Navigation Satellite Systems signals based on the software-defined radio paradigm. The monitoring platform exploits a digital data grabber based on the use of Universal Software Radio Peripheral devices and a satellite navigation fully software receiver; with respect to a traditional commercial receiver, this implementation solution grants a higher level of flexibility for the processing strategy, enabling the possibility of a deeper analysis of the signals in case of meaningful events, such as ionospheric scintillations or radio frequency interference, through the storage of raw samples. Such an implementation approach yields valuable advantages in critical and remote areas, such as polar regions, where resources are limited and installation, maintenance, and replacement of hardware may be critical.

Jamming is the act of intentionally directing powerful electromagnetic waves toward a victim receiver with the ultimate goal of denying its operations. This paper describes the main types of Global Navigation Satellite System (GNSS) jammers and reviews their impact on GNSS receivers. A survey of state-of-the-art methods for jamming detection is also provided. Different detection approaches are investigated with respect to the receiver stage where they can be implemented.

Several location-aware applications rely on the position estimated by means of Global Navigation Satellite Systems (GNSS), which are known to estimate an accurate position in an open environment. However, the quality of the estimated position is degraded in harsh environments in terms of accuracy and reliability. Liability-critical services, such as location-based charging, transportation, and road tolling, are threatened by the use of an unreliable position of the user, and the level of trust in the estimated position has to be considered to avoid a failure of the full service chain. Such an issue is faced by means of integrity monitoring methods in the field of GNSS. However, when dealing with harsh environments, integrity monitoring techniques designed for aeronautical applications would lead to very conservative results and to the rejection of all the positions obtained. Such conservative approach is based on the theoretical error models for the estimation of the pseudorange standard deviation in open sky. The purpose of this work is to propose an innovative method for estimating the pseudorange standard deviation extrapolating it from measurements of observable data, to assess the confidence level in the obtained positions in relation to the real environment surrounding the user. While measuring the pseudorange standard deviation taking into account environment conditions and receiver accuracy, the user is able to achieve better estimation of the user equivalent range error (UERE). Estimating the UERE from raw pseudorange measurements with the proposed run-time method and its subsequent use in the computation of protection levels using the receiver autonomous integrity monitoring (RAIM) algorithm shows significant improvement in navigation system availability by deriving tight protection levels.

The aim of the G-TRAIN project is to set up a framework for higher education addressing different academic (MSc, Specialising Master and PhD) and networking activities. Indeed, it has been identified that on the one hand there are not enough people trained in the field of satellite navigation in Europe to support the finalization of the Galileo system as well as the foreseen development of satellite navigation applications and on the other hand there are no “European GNSS education” only activities. The goal of the project is to set up a long-term model for the coordination of universities, students exchanges and researchers co-operation in order to exploit synergies and to cover all the different needs of GNSS training, expressed by both industry and research worlds. The paper describes the achievements already obtained in the first part of the project lifetime and its future activities.

The advent of the Galileo system in Europe and the modernization plans for global positioning system (GPS) are giving a strong impulse to development of global navigation satellite systems (GNSS). The availability of a variety of new signals is boosting the growth of new services and applications. The next generation of receivers will have to deal with signals in different bandwidths with different modulation schemes. In such a context the reconfigurability offered by software defined radio (SDR) technologies, employing programmable hardware like field programmable gate arrays (FPGAs) and digital signal processors (DSPs), can play an important role. The paper presents a case-study of an efficient hardware/software partitioning for the baseband processor and discusses in detail how to meet the real-time constraints. Finally some results concerning the implementation of the proposed architecture on a prototyping board are given.

The development of context-aware services is strongly pushing the integration of positioning capabilities in personal communication terminals, with particular attention to third generation systems (UMTS). On the other hand, the synergy between communication and positioning can be of aid for this latter easing the acquisition and tracking of weak signals, and improving performance. In order to provide the user of reliable positioning solutions a suitable receiver dealing both with navigation and communication signal is required. A new hybrid positioning algorithm and a joint receiver structure able to receive and process signals broadcast from both navigation satellite systems and cellular radio networks, is presented, discussing the impact on the joint receiver.

There has been a great interest in the development of high-altitude platforms, which are low cost stratospheric aircraft carrying payloads tailored for a wide range of applications in telecommunications and remote sensing. These platforms are capable of flying at altitudes ranging between 17 and 30 km, with a potential endurance of weeks to months, features that make them attractive for the provision of future personal communication services. This paper deals with the theoretical derivation of a channel model for the communication link between the platform and terrestrial mobile users or stations. In particular, we address the problem of modeling the small-scale fading effects. It is shown that the particular geometry of the propagation scenario leads to a specific model applicable to the stratospheric channel.

Abstract The geographical location of a wireless device is acquiring a significant importance under the boost of innovative applications in the wireless market, and under the research activities related to the development of a new generation of Global Navigation Satellite Systems (GNSS). In the US a new phase of the Global Positioning System is foreseen, and Europe has decided to proceed with the Galileo program. In addition, different government institutions worldwide are working toward the definition of navigation plans, and regulations will set as mandatory the location identification of mobile users in emergency situations (US E‐911 law and the European E‐112 directive). Considering all the navigation/positioning systems and techniques that will be available in the near future, it is clear that a central role will be played by the user handset; in fact, if navigation signals from different sources will be available, the unique possibility to obtain the best navigation performance from the user perspective will be the employment of enhanced receivers able to fuse different data. With this aim, this paper presents the design of an innovative navigation receiver based on Software Defined Radio (SDR) technology. The reconfigurability and flexibility issues are guaranteed by the use of reprogrammable high‐speed hardware (FPGA—Field Programmable Gate Array and DSP—Digital Signal Processor) and thus a deep integration at the raw signal level between GPS and the future Galileo has been obtained. The interoperability issue among different systems is then solved at the receiver level. This paper discusses the implementation of a baseline architecture of a reconfigurable GNSS receiver over a FPGA + DSP prototype platform. The receiver is able to deal with different input Signals‐In‐Space (SIS), and can operate with present GPS ranging signals or with the future Galileo SIS. Copyright © 2002 John Wiley & Sons, Ltd.

In recent years great interest has arisen in the development of high altitude platforms (HAP), which are low cost stratospheric aircraft carrying payloads tailored for a wide range of applications within telecommunications and remote sensing. These platforms are able to fly at altitudes ranging between 17 and 20 km, with a potential endurance of weeks to months, features that make them attractive for the provision of future personal communication services. This paper deals with the theoretical derivation of a channel model for the communication link between the platform and terrestrial mobile users or stations. Small scale fading effects are analyzed and due to the particular geometry of the propagation scenario, a specific model for the stratospheric channel is obtained.

The use of orthonormal scaling functions, wavelets and wavelet packets for modulation has recently been proposed. In this paper, we study the performance of different families of wavelets, for modulation over FDM nonlinear satellite channels, and we propose the use of a splitting technique to obtain two-channels modulation schemes with high spectral efficiency. Simulation results indicate that in certain cases the wavelet based shaping pulses could out-perform the traditional techniques in extremely critical transmission conditions, such as interchannel interference impaired satellite transmission.