Forward-scattering radars (FSRs) acquire great interest when low radar cross section (RCS) targets are willing to be detected. This type of radar provides a countermeasure to stealth technology because, here, the targets' RCS depends only on the size and the shape of their silhouette. Passive radars use transmitters of opportunity as signal source, and they are therefore attractive too, due to their inherit low cost. The advantage of considering Global Navigation Satellite System (GNSS) satellites as transmitters of opportunity is the high availability that these satellites offer. Anywhere on earth, around eight Global Positioning System (GPS) satellites are continuously in view. Due to the large number of new GNSS satellites becoming operational in the near future (American GPS, Russian GLONASS, European Galileo system, and Chinese COMPASS), more than 30 satellites are expected to be constantly in view. This provides an optimum scenario for implementation of a GNSS-FSR system. In this paper, experimental results of a GPS-FSR at different target-receiver scenarios near Nuremberg Airport are analyzed. Disturbances on the signals due to diffraction effects, which take place as the targets cross the receiver-satellite baselines, are discussed and evaluated. For these experiments, a hemispherical antenna has been used, which provides promising results for a future GNSS-FSR implementation.

The use of GNSS technologies has been spreading over time up to a point in which a huge diversity of applications require their use. Due to this demand, GNSS has turned into a more reliable technology, as multiple aspects of it have evolved. Integrity has become a vital aspect of being considered when using GNSS. The following document gathers and shows different aspects of integrity in terms of GNSS. The paper mainly focuses on the description of different receiver autonomous integrity monitoring methods. For this purpose, basic concepts and possible GNSS error sources (and their corresponding solutions) are introduced. Afterward, an explanation and a classification of the integrity monitoring techniques is given, where the fault detection and exclusion methods and different protection level computation formulas are analyzed.

Recently, the first successful deployment of a fully automated commercial freight train operation was announced. This is the world’s first automated heavy-duty and long-haul rail network. It’s an impressive achievement, but why has it taken so long to achieve this when driverless urban metros have been in operation for more than 50 years? Although urban metros and freight trains are vehicles moved on rails, their operation and environment differ significantly. Metros operate in closed rail networks, while freight trains operate in open rail networks. However, the same taxonomy is often used to classify automation interchangeably in both environments. This paper provides context and an overview of driving automation in freight rail and reviews the existing taxonomies. This paper starts by providing context with an overview of the general process of driving a vehicle by delimiting its different stages. Next, we describe the overall process of driving a freight train to show the distinctive features of its setup and operation. In this analysis, we will point out the essential differences between open and closed rail networks, and the tasks that can potentially be automated. Additionally, we examine the evolution of level-based automation taxonomies and review those that have been proposed exclusively for driving automation in open and closed railway networks. Our objective is to provide a thorough summarization of the most relevant taxonomies to advance the definition of a suitable taxonomy and framework to classify automation capabilities in rail freight transport and identify some complex challenges ahead.

Most critical applications today depend on computers, so a computer failure can cause financial disaster, serious injury, or even death. In this context, railways are considered a critical application, so they must meet the highest standards of availability and safety. Availability ensures continuous operation of the system, while a safe system must behave correctly in all operating and environmental conditions.

A scalable system for wireless wear monitoring in a distributed harsh industrial environment, in which installation of the electronic equipment near the distributed wearing measuring locations is unfeasible, has been successfully designed, developed and deployed. The system is composed of a novel LC -type passive wireless wear sensor system, a sensor readout coil, an electronic equipment, a readout unit for a scalable multisensor system and a control and monitoring system. The capacitor structure, employed as a sensing device in the LC sensor manufactured on low cost PCB, provides a linear response to the wear level. This allowed us to define a measuring and calibration method to suppress the cable effects from each distributed readout coil to the electronic equipment readout unit. It was possible to achieve a multiple simultaneous measurements in different sensors distributed along an industrial process without significant cabling influence. Concerning the sensor data analysis, a double Holt-Winters method with trend was used to reduce noise effects and an “experience based learning” tool was implemented in order to solve any misbehavior or time lag. Laboratory measurements and on-site operation results in an article mill indicate 1 mm precision and about 0, 5 MHz/mm sensitivity of the LC -type passive wireless wear sensor system.

Independently on the business case addressed, one of the main drawbacks of the railway use cases that need continuous Global Navigation Satellite Systems data is the lack of availability for the 100% of the time of the journey. Additionally, the integrity assessment of the position estimation given is also mandatory for safety critical applications. Thus, tunnels and multipath effects are one of the most challenging situations for the continuous positioning systems. In this context, an autonomous on-board Complementary Positioning System has been proposed to overcome the limitation of Global Navigation Satellite System based positioning systems. This paper proposes a positioning enhancement solution by means of fusing data from the satellite navigation system and inertial measurement units. That hybrid solution provides higher availability and accuracy to the positioning specially on known blocked scenarios, such as tunnels, or urban canyons, by means of a novel environment aware map aided software technique named Known Blocked Scenarios algorithm. This paper describes the Complementary Positioning System and the field test carried out in a challenging environment to validate the enhancement proposed by the authors, which demonstrate the benefits that this system has in known harsh environments for railways.