Sarang Thombre

Today, a substantial portion of global trade is carried by sea. Consequently, the reliance on Global Navigation Satellite System (GNSS)-based navigation in the oceans and inland waterways has been rapidly growing. GNSS is vulnerable to various radio frequency interference. The objective of this research is to propose a resilient Multi-Frequency, Multi-Constellation (MFMC) receiver in the context of maritime navigation to identify any GNSS signal jamming incident and switch to a jamming-free signal immediately. With that goal in mind, the authors implemented a jamming event detector that can identify the start, end, and total duration of the detected jamming event on any of the impacted GNSS signal(s). By utilizing a jamming event detector, the proposed resilient MFMC receiver indeed provides a seamless positioning solution in the event of single-frequency jamming on either the lower or upper L-band. In addition, this manuscript also contains positioning performance analysis of GPS-L5-only, Galileo-E5a-only, and Galileo-E5b-only signals and their multi-GNSS combinations in a maritime operational environment in the Gulf of Finland. The positioning performance of lower L-band GNSS signals in a maritime environment has not been thoroughly investigated as per the authors’ knowledge.

Autonomous ships are expected to improve the level of safety and efficiency in future maritime navigation. Such vessels need perception for two purposes: to perform autonomous situational awareness and to monitor the integrity of the sensor system itself. In order to meet these needs, the perception system must fuse data from novel and traditional perception sensors using Artificial Intelligence (AI) techniques. This article overviews the recognized operational requirements that are imposed on regular and autonomous seafaring vessels, and then proceeds to consider suitable sensors and relevant AI techniques for an operational sensor system. The integration of four sensors families is considered: sensors for precise absolute positioning (Global Navigation Satellite System (GNSS) receivers and Inertial Measurement Unit (IMU)), visual sensors (monocular and stereo cameras), audio sensors (microphones), and sensors for remote-sensing (RADAR and LiDAR). Additionally, sources of auxiliary data, such as Automatic Identification System (AIS) and external data archives are discussed. The perception tasks are related to well-defined problems, such as situational abnormality detection, vessel classification, and localization, that are solvable using AI techniques. Machine learning methods, such as deep learning and Gaussian processes, are identified to be especially relevant for these problems. The different sensors and AI techniques are characterized keeping in view the operational requirements, and some example state-of-the-art options are compared based on accuracy, complexity, required resources, compatibility and adaptability to maritime environment, and especially towards practical realization of autonomous systems.

Today's society is highly reliant on time and frequency synchronization, e.g., in communications systems and financial networks. Precise timing is more and more derived from satellite navigation receivers that are unfortunately very susceptible to various signal threats. We studied the performance of global navigation satellite system (GNSS) timing under different operating conditions and tested the effectiveness of different techniques that improve timing receiver robustness. These features were tested under various threat scenarios related to specific vulnerabilities in GNSS-based timing, such as interference and navigation message errors, and their efficiency was analyzed against the corresponding scenarios. We found that interference or meaconing-type spoofing can threaten GNSS timing, but it can be detected by means of automatic gain control (AGC) and carrier-to-noise ratio-based methods. GNSS interruptions due to interference can be bridged by a local oscillator holdover technique based on a Kalman filter whose parameters are based on a GNSS time solution. Navigation message errors are mitigated by the European Geostationary Navigation Overlay Service (EGNOS), and constellation-wide timing errors can be detected by the use of a dual-constellation [global positioning system (GPS)-Galileo] cross-check. Dual-frequency operation for timing, in addition to mitigating first-order ionospheric effects, was found to be more robust to interference with the option to fall back to single frequency.

GNSS-based applications are susceptible to different threats, including radio frequency interference. Ensuring that the new applications can be validated against the latest threats supports the wider adoption and success of GNSS in higher value markets. Therefore, the availability of standardized GNSS receiver testing procedures is central to developing the next generation of receiver technologies. The EU Horizon2020 research project STRIKE3 (Standardization of GNSS Threat reporting and Receiver testing through International Knowledge Exchange, Experimentation and Exploitation) proposed standardized test procedures to validate different categories of receivers against real-world interferences, detected at different monitoring sites. This paper describes the recorded interference signatures, their use in standardized test procedures, and analyzes the result for two categories of receivers, namely mass-market and professional grade. The result analysis in terms of well-defined receiver key performance indicators showed that performance of both receiver categories was degraded by the selected interference threats, although there was considerable difference in degree and nature of their impact.

Vulnerability of satellite-based navigation signals to intentional and unintentional interference calls for a high-level overview of Global Navigation Satellite System (GNSS) threats occurring globally to understand the magnitude and evolution of the problem. Therefore, a mechanism needs to be developed whereby disparate monitoring systems will be capable of contributing to a common entity of basic information about the threat scenarios they experience. This paper begins with a literature survey of 37 state-of-the-art GNSS threat monitoring systems, which have been analysed based on their respective operational features - constellations monitored and whether they possess the capability to perform interference-type classification, spoofing detection, and interference localisation. Also described is a comparative analysis of four GNSS threat reporting formats in use today. Based on these studies, the paper describes the Horizon2020 Standardisation of GNSS Threat Reporting and Receiver Testing through International Knowledge Exchange, Experimentation and Exploitation (STRIKE3) proposed integrated threat monitoring demonstration system and related standardised threat reporting message, to enable a high-level overview of the prevailing international GNSS threat scenarios and its evolution over time.

The project Enhanced Situational Awareness to Improve Maritime Safety in the Baltic (BONUS ESABALT) studies the feasibility of data crowdsourcing among marine stakeholders in the Baltic Sea for enhancing maritime safety. This paper describes the system architecture, and by use of practical maritime scenarios demonstrates the system utility. These scenarios are categorized under maritime safety, intelligent navigation, and environmental monitoring with cross‐border cross‐sector operability. The paper also summarizes the validation campaign performed onboard Viking Line's cruise ship M/S Amorella, operating between Turku and Stockholm. Analysis of the vessel‐generated data and end‐user requirements recorded during this voyage is expected to enable distillation of the most critical information for crowdsourcing in the maritime scenario. Finally, the paper compares the BONUS ESABALT project with the state‐of‐the‐art and provides the estimated economic and policy impact of the proposed system in the Baltic Sea Region. Copyright © 2016 Institute of Navigation

The Indian Regional Navigation Satellite System (IRNSS) is currently under development with four out of the total planned seven satellites deployed in space. The Department of Navigation and Positioning of the Finnish Geospatial Research Institute (FGI) has been an early adopter of this system in Europe through the development of its software-based multi-frequency multi-GNSS receiver, called FGI-GSRx. This paper presents the results of the first comprehensive IRNSS receiver implementation in Finland, if not in Europe, using the FGI-GSRx receiver. Following a brief description of the IRNSS system, the paper presents the receiver architecture, including the acquisition and tracking stages, and position computation. The results show that IRNSS satellites when used in multi-GNSS positioning can be beneficial in augmenting other satellite systems over north and east Europe. These benefits are expected to grow as more IRNSS satellites are deployed in space in the future. Therefore, the impact of these results is interesting to the positioning, navigation, and timing community even outside the intended service area of IRNSS.