Airborne GNSS Reflectometry for Water Body Detection

This article is dedicated to the study of airborne GNSS-R signal processing techniques for water body detection and edge localization using a low-altitude airborne carrier with high rate reflectivity measurements. A GNSS-R setup on-board a carrier with reduced size and weight was developed for this application. We develop a radar technique for automatic GNSS signal segmentation in order to differentiate in-land water body surfaces based on the reflectivity measurements associated to different areas of reflection. Such measurements are derived from the GNSS signal amplitudes. We adapt a transitional model to characterize the changes in the measurements of the reflected GNSS signals from one area to another. We propose an on-line/off-line change detection algorithm for GNSS signal segmentation. A real flight experimentation took place in the context of this work obtaining reflections from different surfaces and landforms. We show, using the airborne GNSS measurements obtained, that the proposed radar technique detects in-land water body surfaces along the flight trajectory with high temporal (50 Hz ) and spatial resolution (order of 10 to 100 m2). We also show that we can localize the edges of the detected water body surfaces at meter accuracy.

GEODESY, CARTOGRAPHY AND AERIAL PHOTOGRAPHY

The aim of this work is to evaluate the accuracy of determining the wet component of zenith tropospheric delay (ZTD) from GNSS-measurements and the accuracy of determining the hydrostatic component according to the Saastamoinen model in comparison with the radio sounding data as well. Zenith tropospheric delay is determined mainly by two methods - traditional, using radio sounding or using atmospheric models, such as the Saastamoinen model, and the method of GNSS measurements. Determination of the hydrostatic component of the zenith tropospheric delay was performed by radio sounding data obtained at the aerological station Praha-Libus in 2011-2013 and in 2018. Data were processed for the middle decades of January and July of each year at 0h o’clock of the Universal Time. The wet component was calculated from GNSS observations. By a significant number of radio soundings at the Praha-Libus aerological station, hydrostatic and wet components of zenith tropospheric delay (ZTD) and the same number of ZTD values derived for the corresponding time intervals from GNSS measurements at the GOPE reference station were determined. The values of the wet component of ZTD were determined and compared with the corresponding data obtained from radio soundings. We found that the error of the hydrostatic component in winter does not exceed 10 mm in absolute value, and in summer it is approximately 1.5 times smaller. This is due to differences in the stratification of the troposphere and lower stratosphere in winter and summer. As for the wet component of ZTD, its errors do not exceed: in winter 15 mm, in summer – 35 mm. The resulting differences in summer have a negative sign, indicating a systematic shift, and in winter – both negative and positive. Today, there are many studies aimed at improving the accuracy of determining zenith tropospheric delay by both Ukrainian and foreign authors, but the problem of the accuracy of the hydrostatic component remains open. The study provides recommendations for further research to improve the accuracy of zenith tropospheric delay.

GEODESY, CARTOGRAPHY AND AERIAL PHOTOGRAPHY

The aim of the research is to diagnose the metrological characteristics of high-precision GNSS-observations by methods of non-classical error theory of measurements (NETM) based on Ukrainian reference stations. Methodology. We selected 72 GNSS reference stations, downloaded daily observation files from the LPI analysis center server, and created time series in the topocentric coordinate system. The duration of the time series is almost two years (March 24, 2019 - January 2, 2021). Using a specialized software package, the time series have been cleaned of offsets and breaks, seasonal effects, and the trend component has been removed. Verification of empirical distributions of errors was provided by the procedure of NETM on the recommendations offered by G. Jeffries and on the principles of hypothesis tests the theory according to Pearson's criterion. The main result of the research. It is established that the obtained time series of coordinates of reference GNSS stations do not confirm the hypothesis of their conformity to the normal Gaussian distribution law. NETM diagnostics of the accuracy of high-precision GNSS measurements, which is based on the use of confidence intervals for assessing the asymmetry and kurtosis of a significant sample, followed by the Pearson test, confirms the presence of weak, not removed from GNSS-processing, sources of systematic errors. Scientific novelty. The authors use the possibility of NETM to improve the processing of high-precision GNSS measurements and the need to take into account the sources of systematic errors. Failure to take into account certain factors creates the effect of shifting the time coordinate series, which, in turn, leads to subjective estimates of station velocity, i.e. their geodynamic interpretation. Practical significance. Research of the reasons for deviations of errors distribution from the established norms provides metrological literacy of carrying out high-precision GNSS measurements of large samples.

No Perfect Outdoors: Towards a Deep Profiling of GNSS-Based Location Contexts

While both outdoor and indoor localization methods are flourishing, how to properly marry them to offer pervasive localizability in urban areas remains open. Recently, proposals on indoor–outdoor detection have made the first step towards such an integration, yet complicated urban environments render such a binary classification incompetent. Fortunately, the latest developments in Android have granted us access to raw GNSS measurements, which contain far more information than commonly derived GPS location indicators. In this paper, we explore these newly available measurements in order to better characterize diversified urban environments. Essentially, we tackle the challenges introduced by the complex GNSS data and apply a deep learning model to identify representations for respective location contexts. We further develop two preliminary applications of our deep profiling: one, we offer a more fine-grained semantic classification than binary indoor–outdoor detection; and two, we derive a GPS error indicator that is more meaningful than that provided by Google Maps. These results are all corroborated by our extensive data collection and trace-driven evaluations.

Mid-Term Monitoring of Glacier’s Variations with UAVs: The Example of the Belvedere Glacier

Recently, Unmanned Aerial Vehicles (UAV) have opened up unparalleled opportunities for alpine glacier monitoring, as they allow for reconstructing extensive and high-resolution 3D models. In order to evaluate annual ice flow velocities and volume variations, six yearly measurements were carried out between 2015 and 2020 on the debris-covered Belvedere Glacier (Anzasca Valley, Italian Alps) with low-cost fixed-wing UAVs and quadcopters. Every year, ground control points and check points were measured with GNSS. Images acquired from UAV were processed with Structure-from-Motion and Multi-View Stereo algorithms to build photogrammetric models, orthophotos and digital surface models, with decimetric accuracy. Annual glacier velocities were derived by combining manually-tracked features on orthophotos with GNSS measurements. Velocities ranging between 17 m y−1 and 22 my−1 were found in the central part of the glacier, whereas values between 2 m y−1 and 7 my−1 were found in the accumulation area and at the glacier terminus. Between 2 × 106 m3 and 3.5 × 106m3 of ice volume were lost every year. A pair of intra-year measurements (October 2017–July 2018) highlighted that winter and spring volume reduction was ∼1/4 of the average annual ice loss. The Belvedere monitoring activity proved that decimetric-accurate glacier models can be derived with low-cost UAVs and photogrammetry, limiting in-situ operations. Moreover, UAVs require minimal data acquisition costs and allow for great surveying flexibility, compared to traditional techniques. Information about annual flow velocities and ice volume variations of the Belvedere Glacier may have great value for further understanding glacier dynamics, compute mass balances, or it might be used as input for glacier flow modelling.

Experimental Assessment of UWB and Vision-Based Car Cooperative Positioning System

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.

Insights into Seismogenetic Areas in Central Italy from Combined Absolute Gravity and GNSS Measurements

In this study we present and discuss gravity and ground deformation variations, at different time scales, observed in a wide mesh absolute gravity and GNSS network set up in central Italy. The network was installed in the area affected by the 2009 (L’Aquila; Mw 6.1) and 2016 (Amatrice-Norcia; Mw 6.0 and 6.5) seismic activity, in order to verify if gravity and ground deformation variations could be related to seismic effects. The new network includes 5 stations distributed between the Lazio, Umbria, and Abruzzo regions. From 2018 to 2020 three campaigns were carried out using the transportable Micro-g LaCoste FG5#238 and the portable Micro-g LaCoste A10#39 absolute gravimeters and completed with two simultaneous GNSS measurements. Topographic instruments, measurement and analysis techniques enabling accurate measurements in the positioning of the stations and to control their variations over time were applied. The high reliability and accuracy of the absolute gravity data gathered, after being corrected for known effects, showed a negative short-term (2018–2020) pattern throughout the area, up to −30 µGal. Since some stations of the new network coincided with benchmarks already measured in the past, an analysis of long-term gravity changes was carried out and a fair degree of stability was observed in two stations, while positive large variations, of approximately 70 and 157 µGal, were recorded in the other two stations in the time intervals 1954–2020 and 2005–2010, respectively. On the other hand, variations highlighted by GNSS height measurements were all below 3 cm. Here, the first long-lasting gravity measurements carried out with absolute gravimeters in a seismic area in Italy are presented, providing meaningful geophysical information. The obtained results, in terms of availability of a combined absolute gravity and GNSS network, definition of data acquisition and analysis procedures, as well as creation of a high quality data archive, lay the foundations for a multidisciplinary approach towards improving the knowledge of this seismogenetic area of Italy.

GNSS smartphones positioning: advances, challenges, opportunities, and future perspectives

Starting from 2016, the raw Global Navigation Satellite System (GNSS) measurements can be extracted from the Android Nougat (or later) operating systems. Since then, GNSS smartphone positioning has been given much attention. A high number of related publications indicates the importance of the research in this field, as it has been doing in recent years. Due to the cost-effectiveness of the GNSS smartphones, they can be employed in a wide variety of applications such as cadastral surveys, mapping surveying applications, vehicle and pedestrian navigation and etc. However, there are still some challenges regarding the noisy smartphone GNSS observations, the environment effect and smartphone holding modes and the algorithm development part which restrict the users to achieve high-precision smartphone positioning. In this review paper, we overview the research works carried out in this field with a focus on the following aspects: first, to provide a review of fundamental work on raw smartphone observations and quality assessment of GNSS observations from major smart devices including Google Pixel 4, Google Pixel 5, Xiaomi Mi 8 and Samsung Ultra S20 in terms of their signal strengths and carrier-phase continuities, second, to describe the current state of smartphone positioning research field until most recently in 2021 and, last, to summarize major challenges and opportunities in this filed. Finally, the paper is concluded with some remarks as well as future research perspectives.