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This paper presents a prototype, on-water rowing monitoring system and its testing results for a single scull boat. The proposed system aims at recording critical kinetic (athlete biomechanics and oar/seat movements) and kinematic (boat position, velocity, acceleration, and attitude) parameters for sport performance evaluation and rowing technique improvement. The data acquisition unit is organized in two parts: the first part aims at logging boat kinematics based on GNSS/INS filtering, while the second one facilitates kinetics data recording using a series of analog sensors (potentiometers, strain gauges) installed on the athlete’s body and the boat seat and oars. Both parts are connected to a central unit featuring analog voltage digitizers and a micro-PC for device handling and data storing. In order to test the performance of the system a series of field trials were undertaken featuring different observation scenarios as well as intentionally induced errors in the rowing technique. Analysis revealed the high performance of the system in terms of sensor completeness and setup procedures as well as operational efficiency. Moreover, system performance evaluation exercised through studying raw data recordings and resultant parameters at stroke cycle and average (standardized) stroke cycle level confirmed the fruitfulness of the proposed approach and system and its potential for implementation on a broad scale. Finally, the data acquired from the proposed system were used to compute the adopted input parameters and performance indicators to characterize the system in terms of functionality and operational efficiency.

Dynamic characterization and Structural Health Monitoring (SHM) are crucial tools, of increasing demand, for reliable operation and predictive maintenance of large infrastructures, as the percentage of critically ageing infrastructures is growing steadily. We present a minimally invasive and synchronous fiber optic monitoring system for SHM, based on Phase-Optical Time-Domain Reflectometry (Phase-OTDR), and we assess its applicability and performance on a modular Bailey-type bridge of 1 : 2.5 scale. Phase-OTDR systems, along with other fiberoptic-distributed techniques have proven their capabilities in long-range SHM applications, although their complexity and high cost limits drastically their applicability and SHM market penetration. Here, we propose the use of a prototype Phase-OTDR system, featuring customized interrogation instrumentation with a balanced trade-off between performance and cost. Its experimental validation is achieved by comparison with well-established commercial monitoring systems, such as Ground-Based Radar Interferometer (GBRI), laser tracker, and multipoint optical Fiber Bragg Gratings (FBGs), in various excitation conditions and structure-damage scenarios, easily implementable in the model bridge. Finite-element modelling (FEM) and simulations were employed to study the bridge behaviour and provide a reference and comparison framework for the experimental characterization. The Phase-OTDR system successfully detected the structural behaviour in an efficient distributed manner, demonstrating comparable performance to commercial point sensor systems, thus demonstrating its application potential.

Nowadays, Unmanned Aerial Vehicles represent a very popular tool used in dramatically wide range of applications: indeed, their high flexibility, ease of use, and in certain cases quite affordable price make them a very attractive solutions in a number of applications, including surveying and mapping. Despite such a wide range of uses, their usage in automatic/autonomous mode is still restricted by the requirement of the availability of a reliable positioning and navigation system, which in practically all the commercial solutions is represented by the Global Navigation Satellite System (GNSS). Unfortunately, the availability and reliability of GNSS cannot be ensured in all the working conditions of interest. In particular, such condition may not hold downtown, close to high buildings. Since this can also be an operative condition of wide interest, this paper aims at investigating the use of an alternative positioning method that can be integrated with GNSS in order to compensate its unavailability. To be more specific, this paper investigates the positioning performance of an Ultra Wide-Band (UWB) system when an UWB rover is attached to a drone flying close to a building facade, whereas a set of UWB anchors are on the ground, close to the facade. The results obtained in the case study of a building of the University of Padua show that the UWB system positioning performance is quite good (quite less than 1 meter error for most of the time) up to approximately 15–20 meters of distance from the anchors. Close to the top of the building the error significantly increases when using an Extended Kalman filter (EKF) positioning approach, probably mostly due to the low UWB measurement success rate at such heights and to the poor geometric configuration of the UWB network. Nevertheless, a Gauss-Newton-based positioning strategy outperforms the EKF in such critical case, still ensuring errors at 1 meter level.

The increasing demand for reliable indoor navigation systems is leading the research community to investigate various approaches to obtain effective solutions usable with mobile devices. Among the recently proposed strategies, Ultra-Wide Band (UWB) positioning systems are worth to be mentioned because of their good performance in a wide range of operating conditions. However, such performance can be significantly degraded by large UWB range errors; mostly, due to non-line-of-sight (NLOS) measurements. This paper considers the integration of UWB with vision to support navigation and mapping applications. In particular, this work compares positioning results obtained with a simultaneous localization and mapping (SLAM) algorithm, exploiting a standard and a Time-of-Flight (ToF) camera, with those obtained with UWB, and then with the integration of UWB and vision. For the latter, a deep learning-based recognition approach was developed to detect UWB devices in camera frames. Such information is both introduced in the navigation algorithm and used to detect NLOS UWB measurements. The integration of this information allowed a 20% positioning error reduction in this case study.

The articles in this special section focus on recent advancements on the use of the global navigation satellite system (GNSS)-based positioning for intelligent transport systems. The civil applications of geopositioning are undergoing exponential development. The latest market analysis for global navigation satellite systems (GNSSs) shows two major fields of application which share the majority of the market: intelligent transport systems (ITS), mainly in the road ITS domain, and location-based services, accessible on smartphones and tablets. The modernization of GPS and Russia’s GLONASS system and the development of Galileo and Bei- Dou are proceeding at a fast pace, introducing improved potential capabilities and higher performance levels for satellite-based positioning, and leading to new architectures for positioning and new strategies for positioning by means of other sensors. GNSSs are considered the superior system to provide accurate and global position, velocity, and time.

The availability of global navigation satellite systems (GNSS) on consumer devices has caused a dramatic change in every-day life and human behaviour globally. Although GNSS generally performs well outdoors, unavailability, intentional and unintentional threats, and reliability issues still remain. This has motivated the deployment of other complementary sensors in such a way that enables reliable positioning, even in GNSS-challenged environments. Besides sensor integration on a single platform to remedy the lack of GNSS, data sharing between platforms, such as in collaborative positioning, offers further performance improvements for positioning. An essential element of this approach is the availability of internode measurements, which brings in the strength of a geometric network. There are many sensors that can support ranging between platforms, such as LiDAR, camera, radar, and many RF technologies, including UWB, LoRA, 5G, etc. In this paper, to demonstrate the potential of the collaborative positioning technique, we use ultra-wide band (UWB) transceivers and vision data to compensate for the unavailability of GNSS in a terrestrial vehicle urban scenario. In particular, a cooperative positioning approach exploiting both vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) UWB measurements have been developed and tested in an experiment involving four cars. The results show that UWB ranging can be effectively used to determine distances between vehicles (at sub-meter level), and their relative positions, especially when vision data or a sufficient number of V2V ranges are available. The presence of NLOS observations is one of the principal factors causing a decrease in the UWB ranging performance, but modern machine learning tools have shown to be effective in partially eliminating NLOS observations. According to the obtained results, UWB V2I can achieve sub-meter level of accuracy in 2D positioning when GNSS is not available. Combining UWB V2I and GNSS as well V2V ranging may lead to similar results in cooperative positioning. Absolute cooperative positioning of a group of vehicles requires stable V2V ranging and that a certain number of vehicles in the group are provided with V2I ranging data. Results show that meter-level accuracy is achieved when at least two vehicles in the network have V2I data or reliable GNSS measurements, and usually when vehicles lack V2I data but receive V2V ranging to 2–3 vehicles. These working conditions typically ensure the robustness of the solution against undefined rotations. The integration of UWB with vision led to relative positioning results at sub-meter level of accuracy, an improvement of the absolute positioning cooperative results, and a reduction in the number of vehicles required to be provided with V2I or GNSS data to one.

In this paper, we address the challenge of robust indoor positioning using integrated UWB and Wi-Fi measurements. A key limitation of any fusion algorithm is whether the distribution that describes the random errors in the measurements has been correctly specified. Here, we describe the details of a set of practical experiments conducted on a purpose built calibration range, to evaluate the performance of commercial UWB sensors with Wi-Fi measurements as captured by an in-house smartphone application. In this paper, we present comparisons of ranges from the UWB sensors and the Wi-Fi built into the smartphone to true ranges obtained from a robotic total station. This approach is validated in both static and kinematic tests. The calibration range has been established as one component of an indoor laboratory to undertake a more diverse research agenda into robust indoor positioning systems. The experiments presented here have been conducted collaboratively under the joint FIG (WG5.5) and IAG (SC4.2) working groups on multi-sensor systems.

Nowadays, assessing geo-hazards in cultural heritage sites in most cases takes place after the hazard has occurred. Monitoring structural and ground deformation resulting from geo-hazards facilitates the early recognition of potential risks and encourages effective conservation planning. This paper presents an integrated ground deformation monitoring approach based on the combined use of satellite SAR data, campaign-based GPS/GNSS observations, and aerial images from UAVs within the Choirokoitia UNESCO World Heritage Site in Cyprus. The Neolithic settlement of Choirokoitia is one of the most important prehistoric sites in the Eastern Mediterranean. The site is located on a steep hill, which makes it vulnerable to rock falls and landslides. As part of the PROTHEGO project, a series of field measurements were collected at the Choirokoitia site and compared against satellite SAR data to verify kinematic behavior of the broader area and to assist in monitoring potential geo-hazards over time. The results obtained indicate displacement rates of the order of 0.03 m/year. These results indicate that ground deformation should be monitored in the area surrounding the Choirokoitia using long-term, low-impact monitoring systems such as SAR images and UAV-based and geodetic techniques. The combination of such monitoring technologies can be compared to monitor and assess potential geo-hazards on archeological sites with increased accuracy. This paper was developed under the auspices of the activities of the “ERATOSTHENES: Excellence Research Centre for Earth Surveillance and Space-Based Monitoring of the Environment”- “EXCELSIOR” project that has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No. 857510 and from the Government of the Republic of Cyprus through the Directorate General for the European Programmes, Coordination and Development. From 1 October 2019, the ERC group (Department of Civil Engineering and Geomatics) at the Cyprus University of Technology is on the way to be upgraded to ERATOSTHENES Centre of Excellence (ECoE) through “EXCELSIOR” H 2020 Widespread Teaming project ( www.excelsior2020.eu ). The project “Cyprus Continuously Operating Natural Hazards Monitoring and Prevention System” (CyCLOPS) RPF/INFRASTRUCTURES/1216 /0050 is co-financed by the European Regional Development Fund and the Republic of Cyprus through the Research Promotion Foundation in the framework of the RESTART 2016-2020 Research Programme. The “PROTection of European Cultural HEritage from GeO-hazards (PROTHEGO)” project HERITAGE PLUS/0314/36 is funded in the framework of the Joint Programming Initiative on Cultural Heritage and Global Change (JPICH) – HERITAGE PLUS under ERA-NET Plus and the Seventh Framework Programme (FP7) of the European Commission and the Cyprus Research Promotion Foundation, contract KOINA/ΠΚΠ-HERITAGE PLUS/0314/36.

Localization in GNSS-denied/challenged indoor/outdoor and transitional environments represents a challenging research problem. As part of the joint IAG/FIG Working Groups 4.1.1 and 5.5 on Multi-sensor Systems, a benchmarking measurement campaign was conducted at The Ohio State University. Initial experiments have demonstrated that Cooperative Localization (CL) is extremely useful for positioning and navigation of platforms navigating in swarms or networks. In the data acquisition campaign, multiple sensor platforms, including vehicles, bicyclists and pedestrians were equipped with combinations of GNSS, Ultra-wide Band (UWB), Wireless Fidelity (Wi-Fi), Raspberry Pi units, cameras, Light Detection and Ranging (LiDAR) and inertial sensors for CL. Pedestrians wore a specially designed helmet equipped with some of these sensors. An overview of the experimental configurations, test scenarios, characteristics and sensor specifications is given. It has been demonstrated that all involved sensor platforms in the different test scenarios have gained a significant increase in positioning accuracy by using ubiquitous user localization. For example, in the indoor environment, success rates of approximately 97% were obtained using Wi-Fi fingerprinting for correctly detecting the room-level location of the user. Using UWB, decimeter-level positioning accuracy is demonstrable achievable under certain conditions. The full sets of data is being made available to the wider research community through the WG on request.

Global navigation satellite systems (GNSS) has become a kind of positioning standard due to the high penetration rate of this technology on mass market intelligent transportation systems (ITS) applications. However, this positioning technique remains a real challenge for very demanding ITS services which require continuity and a specific accuracy of the data. This study reports on a practical and methodological approach for the evaluation of the GNSS and multi-sensors positioning and attitude of vehicles in real life conditions. Test scenarios have been set up with several positioning sensors mounted on a vehicle for the collection of raw data on different road sections. The measurement of a high quality reference trajectory with an accuracy of several centimetres allows to estimate position accuracy under different environmental conditions. The authors will show in detail the results and identify some typical situations (e.g. sub-urban environment) where the quality of positioning parameters is reduced to several metres instead of dm and may impact the level of ITS services, e.g. road user charging or safety applications. This study results from the methodology developed in the satellite positioning performance assessment for road applications COST Action on the performance assessment of positioning terminals for ITS.

Global navigation satellite systems have tremendous impact and potential in the development of intelligent transportation systems and mobility services and are expected to deliver significant benefits, including increased capacity, improved safety, and decreased pollution. However, there are situations in which there might not be direct location information about vehicles, for example, in tunnels and in indoor facilities such as parking garages and commercial vehicle depots. Various technologies can be used for vehicle localization in these cases, and other sensors that are currently available in most modern smartphones, such as accelerometers and gyroscopes, can be used to obtain information directly about the driving patterns of individual drivers. The objective of this research is to present a framework for vehicle localization and modeling of driving behavior in indoor facilities or, more generally, facilities in which global navigation satellite system information is not available. Localization technologies and needs are surveyed and the adopted methodology is described. The case studies, which use data from multiple types of sensors (including accelerometers and gyroscopes from two smartphone platforms as well as two reference platforms), provide evidence that the opportunistic smart-phone sensors can be useful in identifying obstacles (e.g., speed humps) and maneuvers (e.g., U-turns and sharp turns). These data, when cross-referenced with a digital map of the facility, can be useful in positioning the vehicles in indoor environments. At a more macroscopic level, a methodology is presented and applied to determine the optimal number of clusters for the drivers’ behavior with a mix of suitable indexes.

Cooperative positioning (CP) utilises information sharing among multiple nodes to enable positioning in Global Navigation Satellite System (GNSS)-denied environments. This paper reports the performance of a CP system for pedestrians using Ultra-Wide Band (UWB) technology in GNSS-denied environments. This data set was collected as part of a benchmarking measurement campaign carried out at the Ohio State University in October 2017. Pedestrians were equipped with a variety of sensors, including two different UWB systems, on a specially designed helmet serving as a mobile multi-sensor platform for CP. Different users were walking in stop-and-go mode along trajectories with predefined checkpoints and under various challenging environments. In the developed CP network, both Peer-to-Infrastructure (P2I) and Peer-to-Peer (P2P) measurements are used for positioning of the pedestrians. It is realised that the proposed system can achieve decimetre-level accuracies (on average, around 20 cm) in the complete absence of GNSS signals, provided that the measurements from infrastructure nodes are available and the network geometry is good. In the absence of these good conditions, the results show that the average accuracy degrades to meter level. Further, it is experimentally demonstrated that inclusion of P2P cooperative range observations further enhances the positioning accuracy and, in extreme cases when only one infrastructure measurement is available, P2P CP may reduce positioning errors by up to 95 % . The complete test setup, the methodology for development, and data collection are discussed in this paper. In the next version of this system, additional observations such as the Wi-Fi, camera, and other signals of opportunity will be included.

This paper describes a new algorithm to aid stand-alone GNSS positioning in areas of bad signal reception using a Digital Elevation Model (DEM). Traditional Height-Aiding (HA) algorithms assume either a preset (fixed) value for the receiver elevation or rely on the elevation value that corresponds to the nearest available position fix. This may lead in erroneous receiver elevation estimates that, under circumstances, are inefficient to aid effectively GNSS positioning. In this study, the receiver elevation is updated at every iteration step of the navigation solution through dynamic interpolation of the elevation model. The algorithm, because of its ability to extract and fully exploit the elevation information derived from a digital model, it can prove particularly useful in forested areas with steep-sloped terrain. Extended test runs were undertaken to validate the correctness of the mathematical model and the feasibility of the algorithm and associated software. Particularly, analysis of a dataset acquired in a forested, rapidly undulating environment reveals significant average improvement in all performance metrics of positioning, namely the GNSS position availability (50%), accuracy (56%) and external reliability (86%) compared to the Standard Point Positioning (SPP) solution. Moreover, it was found that the method can cope successfully in marginal operating conditions with situations of bad satellite geometry and satellite signals affected by interference due to tree canopy. © 2013 COSPAR. Published by Elsevier Ltd. All rights reserved.

PNT stands for Positioning, Navigation, and Timing. Space-based PNT refers to the capabilities enabled by GNSS, and enhanced by Ground and Space-based Augmentation Systems (GBAS and SBAS), which provide position, velocity, and timing information to an unlimited number of users around the world, allowing every user to operate in the same reference system and timing standard. Such information has become increasingly critical to the security, safety, prosperity, and overall qualityof-life of many citizens. As a result, space-based PNT is now widely recognized as an essential element of the global information infrastructure. This paper discusses the importance of the availability and continuity of PNT information, whose application, scope and significance have exploded in the past 10–15 years. A paradigm shift in the navigation solution has been observed in recent years. It has been manifested by an evolution from traditional single sensor-based solutions, to multiple sensor-based solutions and ultimately to collaborative navigation and layered sensing, using non-traditional sensors and techniques – so called signals of opportunity. A joint working group under the auspices of the International Federation of Surveyors (FIG) and the International Association of Geodesy (IAG), entitled ‘Ubiquitous Positioning Systems’ investigated the use of Collaborative Positioning (CP) through several field trials over the past four years. In this paper, the concept of CP is discussed in detail and selected results of these experiments are presented. It is demonstrated here, that CP is a viable solution if a ‘network’ or ‘neighbourhood’ of users is to be positioned / navigated together, as it increases the accuracy, integrity, availability, and continuity of the PNT information for all users.

This paper studies the long-term (>30 years) settlement behavior of the Mornos dam on the basis of finite element analysis and vertical displacement data. It compares actually measured deformations resulting from a continuous geodetic monitoring record of the dam behavior with a numerical back analysis. Our aim is to explain the actual deformation history on the basis of the mechanical behavior of the dam. The deformation monitoring record consists of precise leveling data of a large number of control stations established along the crest and the inspection gallery of the dam, as well as settlements derived by magnetic extensometers placed inside the dam body. Overall, the available data cover the phases of construction, first filling of the reservoir and most of the operational time of the dam. The numerical modeling assumes 2D plane-strain conditions to obtain the displacement and the stress–strain characteristics of the abutments and the dam at eleven equally-spaced cross sections. Comparative evaluation of the results of the geodetic monitoring analysis against the findings from the finite element back analysis simulating characteristic stages in the lifetime of the structure, shows a very good agreement (on average 0.03 m) between the measured and computed displacements, which testifies to the correctness of the geotechnical parameters and loads used in the analysis.

2013 10th Workshop on Positioning, Navigation and Communication, WPNC 2013 - Proceedings 2013, Article number 6533262 Collaborative (or cooperative) positioning or navigation uses multiple location sensors with different accuracy on different platforms for sharing of their absolute and relative localizations. Typical application scenarios are dismounted soldiers, swarms of UAV's, team of robots, emergency crews and first responders. This paper studies the challenges to realize a public and low-cost solution, based on mass users of multiple-sensor platforms. For the investigation field experiments revolved around the concept of collaborative navigation in a week at the University of Nottingham in May 2012. Different sensor platforms have been fitted with similar type of sensors, such as geodetic and low-cost high-sensitivity GNSS receivers, tactical grade IMU's, MEMS-based IMU's, miscellaneous sensors, including magnetometers, barometric pressure and step sensors, as well as image sensors, such as digital cameras and Flash LiDAR, and ultra-wide band (UWB) receivers. The employed platforms in the tests include a train on a building roof, mobile mapping vans and personal navigators. The presented preliminary results of the field experiments show that a positioning accuracy on the few meter level can be achieved for the navigation of the different platforms. © 2013 IEEE.

2012 International Conference on Indoor Positioning and Indoor Navigation, IPIN 2012 - Conference Proceedings 2012, Article number 6418893 An integrated positioning solution termed 'collaborative positioning' employs multiple location sensors with different accuracy on different platforms for sharing of their absolute and relative localizations. Typical application scenarios are dismounted soldiers, swarms of UAV's, team of robots, emergency crews and first responders. The stakeholders of the solution (i.e., mobile sensors, users, fixed stations and external databases) are involved in an iterative algorithm to estimate or improve the accuracy of each node's position based on statistical models. This paper studies the challenges to realize a public and low-cost solution, based on mass users of multiple-sensor platforms. For the investigation field experiments revolved around the concept of collaborative navigation, and partially indoor navigation. For this purpose different sensor platforms have been fitted with similar type of sensors, such as geodetic and low-cost high-sensitivity GNSS receivers, tactical grade IMU's, MEMS-based IMU's, miscellaneous sensors, including magnetometers, barometric pressure and step sensors, as well as image sensors, such as digital cameras and Flash LiDAR, and ultra-wide band (UWB) receivers. The employed platforms in the tests include a train on a building roof, mobile mapping vans, a personal navigator and a foot tracker unit. In terms of the tests, the data from the different platforms are recorded simultaneously. Several field experiments conducted in a week at the University of Nottingham are described and investigated in the paper. The personal navigator and a foot tracker unit moved on the building roof, then trough the building down to where it logged data simultaneously with the vans, all of them moving together and relative to each other. The platforms then logged data simultaneously covering various accelerations, dynamics, etc. over longer trajectories. Promising preliminary results of the field experiments showed that a positioning accuracy on the few meter level can be achieved for the navigation of the different platforms. © 2012 IEEE.