R-Mode Baltic - A User Need Driven Testbed Development for the Baltic Sea

During the past few decades, the presence of global navigation satellite systems (GNSSs) such as GPS, GLONASS, Beidou and Galileo has facilitated positioning, navigation and timing (PNT) for various outdoor applications. With the rapid increase in the number of orbiting satellites per GNSS, enhancements in the satellite-based augmentation systems (SBASs) such as EGNOS and WAAS, as well as commissioning new GNSS constellations, the PNT capabilities are maximized to reach new frontiers. Additionally, the recent developments in precise point positioning (PPP) and real time kinematic (RTK) algorithms have provided more feasibility to carrier-phase precision positioning solutions up to the third-dimensional localization. With the rapid growth of internet of things (IoT) applications, seamless navigation becomes very crucial for numerous PNT dependent applications especially in sensitive fields such as safety and industrial applications. Throughout the years, GNSSs have maintained sufficiently acceptable performance in PNT, in RTK and PPP applications however GNSS experienced major challenges in some complicated signal environments. In many scenarios, GNSS signal suffers deterioration due to multipath fading and attenuation in densely obscured environments that comprise stout obstructions. Recently, there has been a growing demand e.g. in the autonomous-things domain in adopting reliable systems that accurately estimate position, velocity and time (PVT) observables. Such demand in many applications also facilitates the retrieval of information about the six degrees of freedom (6-DOF - x, y, z, roll, pitch, and heading) movements of the target anchors. Numerous modern applications are regarded as beneficiaries of precise PNT solutions such as the unmanned aerial vehicles (UAV), the automatic guided vehicles (AGV) and the intelligent transportation system (ITS). Hence, multi-sensor fusion technology has become very vital in seamless navigation systems owing to its complementary capabilities to GNSSs. Fusion-based positioning in multi-sensor technology comprises the use of multiple sensors measurements for further refinement in addition to the primary GNSS, which results in high precision and less erroneous localization. Inertial navigation systems (INSs) and their inertial measurement units (IMUs) are the most commonly used technologies for augmenting GNSS in multi-sensor integrated systems. In this article, we survey the most recent literature on multi-sensor GNSS technology for seamless navigation. We provide an overall perspective for the advantages, the challenges and the recent developments of the fusion-based GNSS navigation realm as well as analyze the gap between scientific advances and commercial offerings. INS/GNSS and IMU/GNSS systems have proven to be very reliable in GNSS-denied environments where satellite signal degradation is at its peak, that is why both integrated systems are very abundant in the relevant literature. In addition, the light detection and ranging (LiDAR) systems are widely adopted in the literature for its capability to provide 6-DOF to mobile vehicles and autonomous robots. LiDARs are very accurate systems however they are not suitable for low-cost positioning due to the expensive initial costs. Moreover, several other techniques from the radio frequency (RF) spectrum are utilized as multi-sensor systems such as cellular networks, WiFi, ultra-wideband (UWB) and Bluetooth. The cellular-based systems are very suitable for outdoor navigation applications while WiFi-based, UWB-based and Bluetooth-based systems are efficient in indoor positioning systems (IPS). However, to achieve reliable PVT estimations in multi-sensor GNSS navigation, optimal algorithms should be developed to mitigate the estimation errors resulting from non-line-of-sight (NLOS) GNSS situations. Examples of the most commonly used algorithms for trilateration-based positioning are Kalman filters, weighted least square (WLS), particle filters (PF) and many other hybrid algorithms by mixing one or more algorithms together. In this paper, the reviewed articles under study and comparison are presented by highlighting their motivation, the methodology of implementation, the modelling utilized and the performed experiments. Then they are assessed with respect to the published results focusing on achieved accuracy, robustness and overall implementation cost-benefits as performance metrics. Our summarizing survey assesses the most promising, highly ranked and recent articles that comprise insights into the future of GNSS technology with multi-sensor fusion technique.

Ship navigation requires accurate positioning, navigation and timing (PNT) data. PNT data from a single source has uncertainties and potential risks. Wrong PNT data has a huge impact on ship maneuvering, and at the same time, it may cause huge losses to national assets and national security. This chapter proposes a data fusion algorithm based on single-frequency global navigation satellite system (GNSS) and inertial navigation system (INS) to obtain PNT data, which can improve the availability, accuracy, reliability, continuity, and robustness. The experimental results show that the data fusion method combining median filtering and Kalman filtering can improve the system's ability to acquire PNT data. When blocking GNSS acquisition of PNT data, relying on INS, you can still obtain PNT data, which can make up for the ability to obtain PNT data from GNSS.

Currently Global Navigation Satellite Systems (GNSS) are the primary source for the determination of absolute position, velocity and time (PVT) for merchant vessel navigation. On a ship bridge a number of systems like Electronic Chart and Information Systems (ECDIS), automatic track control systems and the Automatic Identification System (AIS) are relying on that PVT provision. Nevertheless it is well known that GNSS performance can strongly degrade due to space weather events, jamming and spoofing. Especially the availability and usage of low cost jammers, so called personal privacy devices (PPD), lead to the question on how a continuous onboard provision of PVT data can be realized in the presence of such a PPD jammer. Generally three possible solutions for that challenge are contemplated: i) the usage of a terrestrial backup system, ii) a jamming resistant GNSS receiver or iii) the integration of GNSS with other onboard self-contained navigation sensors like, e.g. speed log, gyrocompass and inertial sensors (Inertial Measurement Unit - IMU). The paper will focus on option (iii) and addresses the question whether it is possible to bridge real maritime GNSS Jamming attacks by a Kalman Filter (KF) using GNSS, inertial and Doppler velocity log (DVL). The main challenge for the KF here is, that a free inertial integration needs to be performed after a time period with already degraded GNSS signal reception. As KF are known to be optimum estimators only under the assumption of known statistics of the measurements, the question arises, whether the pseudoranges under the influence of jamming still follow a certain statistics. In order answer this question an additional lab experiment was performed and analyzed. Concretely the sensor fusion was realized by using both loosely and tightly coupled architectures which have been implemented using an Unscented Kalman Filter (UKF). The fusion algorithm is formulated in ECEF coordinate frame with quaternion attitude parameterization, where the heading observability is addressed by fusing the baseline measurements from the GNSS compass. In order to evaluate the performance of the proposed sensor fusion scheme under the influence of a real maritime jamming attack we performed an experiment in our civilian maritime jamming testbed in the Baltic, which has been established together with the German Federal Network Agency approximately 6 nmi north of the peninsula Dars. Here a PPD jammer was mounted on the monkey deck of an anchored vessel. A test vessel was maneuvering around the jammer. As a test vessel the multipurpose research and diving vessel Baltic Diver II (length 29 m, beam 6.7 m and draught 2.8 m) was used, which was equipped with three dual frequency GNSS receivers, a fiber-optic gyroscope IMU and a Doppler velocity log. The obtained results confirm that real maritime jamming attacks using PPD Jammers can be bridged by the proposed tightly coupled GNSS-IMU-DVL integration scheme resulting in horizontal position errors of less than 10m only.

Positioning, Navigation and Timing (PNT) services based on the Global Navigation Satellite System (GNSS) have a number of known drawbacks that makes them prone to suffer a disruption. These flaws can be exploited to disable this service in critical infrastructures. Therefore, the hybridization of GNSS and 5G measurements enabling Assured PNT (APNT) services is growing up and gaining attention by governmental bodies. 5G signals emitted by terrestrial networks and by Low Earth Orbit (LEO) satellites can complement GNSS, enhancing their reliability, security and accuracy. For example, the larger Signal-to-Noise Ratio (SNR) of a terrestrial system makes them more difficult to suffer a jamming attack as compared to GNSS signals. A joint data and positioning signal enhances the security and reliability of the APNT solution with, for example, the successful decoding of encrypted data, this could be used for system authentication. Moreover, a larger signal bandwidth increases the accuracy of the PNT solution. All of these benefits can be extracted from the 5G terrestrial and non-terrestrial networks that transmit the Positioning Reference Signal (PRS). The rationale for these benefits rely on the flexibility of this pilot signal in terms of bandwidth or symbols used for the APNT service. This paper aims to analyse how this flexibility can be optimized to achieve a specific level of accuracy, minimizing the resources used under certain constrains of bandwidth or latency. The results present the optimal parameters to design a 5G PRS waveform with a target scenario constrains. Then, we compare it with the GNSS service and how to benefit when using them in combination. Finally, the paper concludes with the future research lines proposing a joint communications and positioning system as a closed loop. In such scenario, the user achieved accuracy is sent back to the infrastructure, and using the dynamic PRS flexibility, the system increases or reduces the PRS resources in order to meet the user accuracy requirements.

A wide-range utilisation of Global Navigation Satellite Systems (GNSS) across technology and socioeconomic domains renders the satellite navigation one of the pillars of the modern civilisation. Tackling and overcoming The inherent shortcomings and emerging threats to provision of robust and resilient GNSS Positioning, Navigation and Timing (PNT) services have become a research subject of the utmost importance. An open access to the GNSS positioning estimation process is fundamental for development of advanced methods for robust and resilient GNSS position estimation. Recent introduction of Google Android 7.0 revision allows for direct access to raw GNSS pseudoranges observed by smartphones. Here we address the opportunities for GNSS positioning estimation improvements, given through exploitation of Google Android Location API, in creation of bespoke GNSS position estimation process in navigation application domain of a GNSS Software-Defined Radio (SDR) receivers in smartphones. We present and validate opportunities for improvement of GNSS position estimation process through utilisation of distributed computing architectures, trusted sources of GNSS augmentation data and utilisation of GNSS positioning methods suitable for targeted classes of GNSS applications Authors are members of European GNSS Agency's GNSS Raw Measurements Task Force, and co-authored the white-paper on GNSS-related Google Android Location API applications.

Position, Navigation and Timing (PNT) is integral to the safety, security and prosperity of the United Kingdom, its Overseas Territories, and wider global interests. PNT is also critical to the UK’s national security supporting command, control, and communications capabilities, and to the cyber enterprise. The loss of PNT services from modalities such as Global Navigation Satellite Systems (GNSS) (like the US Global Positioning System (GPS)) will have a significant impact on our economic wellbeing. This paper describes the development of a framework for the coordination of PNT across the UK Government and for the wider UK. It proposes both a strategic and integrated system-of-system architecture that addresses how to bring the complex area of policy, strategy, skills, legislation, delivery mechanisms and multiple technologies, including research and development, together in a coherent way, integrating existing programmes, as well as proposes how to determine appropriate technology approaches looking to the future. It is the core outcome of an evidence based comprehensive review and PNT Strategy development in the UK with the goal to ensure PNT users have access to resilient and assured PNT services when they need them.

Aimed at addressing the problem of carrier synchronization for satellite-based Automatic Identification System (AIS) signals, a novel data-aided carrier frequency offset estimation method in the intermediate frequency is proposed in this paper. AIS signals use Gaussian Minimum Shift Keying (GMSK) for transmission, and a nonlinearity of the GMSK signal is shown to be a sine wave with frequency related to the carrier frequency offset. Based on that, this method constructs an auxiliary function with the available symbols to avoid the influence of the modulated phase information, and it estimates the frequency offset due to Doppler shift with a new interpolated FFT method. Moreover, this method performs better when the signals are filtered by band pass filter even through the bandwidth is as low as the 1/3 nominal bandwidth. Computer simulations are used to assess the synchronizer performance on AWGN channels.

In order to verify the feasibility of atmospheric duct inversion method using automatic identification system signal in the actual sea area, a sea experiment was carried out. The signal acquisition system of portable high sensitivity civil automatic identification system is developed, and the receiving and processing process of automatic identification system signal is analysed. The sea experiment scheme and main experiment equipment are given, and the collected experiment data are processed and analysed. Finally, the method of atmospheric duct inversion using automatic identification system signal is verified by the measured data. Atmospheric duct inversion is an inverse problem, which requires the use of various optimisation algorithms to optimise the duct parameters in order to obtain the characteristic parameter information of the duct. In this paper, the Lévy flight quantum‐behaved particle swarm optimisation algorithm and the deep learning algorithm are respectively used to invert the atmospheric duct parameters. The results show that there is little difference between the inverted duct parameters and the true duct parameters, which verifies the feasibility of using the automatic identification system signal to invert the atmospheric duct.

The advent of Global Navigation Satellite Systems (GNSS) initiated a revolution in Positioning, Navigation and Timing (PNT) applications. Besides the enormous impact on geospatial data acquisition and reality capture, satellite navigation has penetrated everyday life, a fact which is proved by the increasing degree of human reliance on GNSS-enabled smart devices to perform casual activities. Nevertheless, GNSS does not perform well in all cases. Specifically, in GNSS-challenging environments, such as urban canyons or forested areas, navigation performance may be significantly degraded or even nullified. Consequently, positioning is achieved by combining GNSS with additional heterogeneous information or sensors, such as inertial sensors. To date, most smartphones are equipped with at least accelerometers and gyroscopes, besides GNSS chipsets. In the frame of this research, difficult localization scenarios were investigated to assess the performance of these low-cost inertial sensors with respect to higher grade GNSS and IMU systems. Four state-of-the-art smartphones were mounted on a specifically designed on-purpose build platform along with reference equipment. The platform was installed on top of a vehicle, which was driven by a predefined trajectory that included several GNSS-challenging parts. Consequently, positioning and inertial readings were acquired by smartphones and compared to the information collected by the reference equipment. The results indicated that although the smartphone GNSS receivers have increased sensitivity, they were unable to produce an acceptable solution for more than 30% of the driven course. However, all smartphones managed to identify, up to a satisfactory degree, distinct driving features, such as curves or bumps.

In urban canyons, the positioning accuracy obtainable from global navigation satellite systems (GNSS) is mainly impaired by signal interference due to multipath and non-lineof-sight (NLOS) effects. GNSS is one of the sensors used in connected autonomous vehicles (CAVs) for positioning, navigation and timing (PNT). Hence, it is essential that GNSS receivers in CAVs are robust and resilient. In this paper, a method consisting of two layers of GNSS observation checks is suggested to exclude these effects in order to improve the positioning accuracy. The first layer excludes all non-consistent measurements identified by a chi-square test threshold. The second layer uses a decision tree for the exclusion of any remaining multipath/NLOS affected measurements, based on a data set obtained from a ray tracer for a 3D mapped model environment. The simulation results show an enhancement in positioning accuracy greater than 95%.

With the rapid development of global industry, AIS (automatic identification system) has become an important tool for ship management and safety monitoring. In order to better display the frequency distribution of AIS signals, this paper graphically displays the data in the AIS signals, allowing users to fully understand the data in the AIS signals, including ship type distribution, speed range, and signal frequencies in different areas. It uses Kafka and Flink technology to receive, clean and analyze the sent data, and finally stores it in MySQL and Redis data. It reads the data through Spring Boot + MyBatis, and uses Vue + Echarts chart tool and AutoNavi Map API for display and analysis. To gain an in-depth understanding of its importance and application prospects in the field of epidemics.

Global Navigation Satellite Systems (GNSSs) are by far the most widespread technology for Position Navigation and Timing (PNT). They have been traditionally deployed exploiting Medium Earth Orbit (MEO) or Geostationary Earth Orbit (GEO) satellite constellations. To meet future demands and overcome MEO and GEO limitations, GNSSs based on Low Earth Orbit (LEO) constellations have been investigated as a radical system change. Although characterized by a higher Doppler effect, a PNT service supplied by means of LEO satellites can provide received signals that are about 30 dB stronger. Moreover, existing LEO constellations and the forthcoming mega-constellations, which are designed for broadband internet coverage, can be exploited to provide a piggybacked PNT service. With this cost-effective solution, a secondary PNT service might be subject to an economical use of resources, which may result in substantial bandwidth limitations. At the same time, the introduction of meta-signals in the GNSS literature has brought a new receiver signal processing strategy, particularly effective in terms of available bandwidth exploitation. It allows to increase the positioning accuracy exploiting a wideband processing approach, which might be challenging under severe Doppler conditions. A narrowband implementation of the meta-signal concept, namely Virtual Wideband (VWB) can tolerate harsh Doppler conditions while also reducing the processed bandwidth. It is thus more effective when addressing a secondary PNT service, where a limited frequency occupation might be an essential requirement. The aim of this work is to show the applicability of a VWB receiver architecture on signals provided by a piggybacked PNT service, hosted on a broadband LEO constellation. We demonstrate the capability of this implementation to bear high Doppler conditions while empowering the potential of LEO PNT.

Our modern world is interconnected with advanced technologies. All aspects of our lives are dependent on our ability to measure space and time every day. “Where are we and what time is it”? These two basic questions connect us to all aspects of our modern, technologically driven lives. Satellites, in this case, Global Navigation Satellite Systems (GNSS) also known as Positioning Navigation and Timing (PNT) satellites, have quickly become an integral part of our daily lives and are now an unseen but vital utility that is used throughout the world. A day without GNSS satellites would be a very bad day indeed. Most people in the world use GNSS systems every day, without even knowing it. Only when it disappeared would they understand just how much they depend on it for carrying out their daily activities.

The global navigation satellite system (GNSS) signal modulation type plays a crucial role in determining the performances of positioning, navigation and timing (PNT) services. Currently, the binary offset carrier (BOC) modulation signal and binary coded symbol (BCS) modulation signal are both bipolar signals, which greatly restrict the room of improving the GNSS signal performance. Therefore, multi-level coded symbol (MCS) modulation has received great attention in the field of GNSS signal design. The MCS modulation is the most extensive step-coded symbol modulation mode, where BOC modulation and BCS modulation are its special cases. Since the waveform symbol of the MCS modulation signal can be arbitrarily valued, the optimal GNSS signal can be designed. However, like the BOC modulation signal, the MCS modulation signal also has the problem of ambiguous tracking, and then results in a large pseudo range measurement error, which is unacceptable for the new generation GNSS with high accuracy. In recent years, the unambiguous tracking of GNSS signals has become a hot research subject in the navigation signal processing domain and many methods are presented, and those methods can be divided into three categories:BPSK-like method, bump jump (BJ) method, and side-peak cancellation (SC) method. However, these methods are designed for BOC signal, and they are not suitable for MCS signal. Therefore, in this paper we propose a general unambiguous tracking algorithm based on the pseudo correlation function (PCF), which is suitable for MCS modulated signals. Firstly, the unitary expression of MCS modulated signal based on waveform value vector is given, then the unitary formula of cross-correlation function for MCS signal is derived and the definition of PCF is given. Then the constraint condition which should be satisfied to realize unambiguous tracking is analyzed in depth, and the universal constructing method of two reference signals and the relationship between each other are derived according to this constraint condition, which brings great convenience for solving the specific MCS signal. The code tracking loop model of GNSS receiver based on the proposed method is illustrated. It is observed that the proposed method can receive different MCS signals under the same receiver loop framework, and can simplify the design of the receiver while eliminating the tracking ambiguous problem. Finally, as a special case of MCS signal, the applications of the proposed method in four kinds of BOC signals are discussed respectively, and then the waveform value vector of the reference signal and the unitary expression of code discriminator are derived. Simulation results show that the proposed method can effectively solve the ambiguous tracking problem of MCS signal, which has good performance and broad application prospect.

Versions of this paper were first presented at the Royal Institute of Navigation GNSS Vulnerabilities and Solutions Conference held at Baska, Croatia in September 2008 and the Royal Institute of Navigation NAV 08 Conference held at Church House, Westminster, London in October 2008.The US Global Positioning System (GPS) is currently the primary source of Position, Navigation and Timing (PNT) information in maritime applications, whether stand-alone or augmented with additional systems. This situation will continue in the future with GPS, possibly together with other Global Navigation Satellite Systems (GNSS) e.g. Galileo, being the core PNT technology for e-Navigation – the future digital maritime architecture. GPS signals, measured at the surface on the Earth, are very weak. As such, the system is vulnerable to unintentional interference and jamming, resulting in possible denial of service over large geographical areas. The result of such interference could be the complete failure of the mariner's GPS receiver or, possibly worse, the presentation to the mariner of hazardously misleading information (HMI) for navigation and situational awareness, depending on how the GPS receiver reacts to the jamming incident. Recognising this, the General Lighthouse Authorities of the United Kingdom and Ireland (GLA), in collaboration with the UK Ministry of Defence (MOD) Defence Science and Technology Laboratory (DSTL), have conducted a series of sea-trials with the aim of identifying the full effects of GPS jamming on safe navigation at sea.This paper presents the key findings of these trials and provides important information on the effect of GPS denial. The GLA are playing a pivotal role in the establishment of eLoran as an independent source of PNT, taking advantage of eLoran's complementary nature, having dissimilar failure modes to GPS and the future GNSS. This paper provides information on the performance of an eLoran receiver in an area of GPS service denial. The paper presents the rationale for the work, details the system architecture employed, the data gathering efforts and finally the data analysis procedures, results and conclusions.