This letter presents a radiation pattern verification system for low-frequency antennas in their operative conditions, e.g., on the ground, next to other elements, etc. It is a far-field setup using a properly equipped micro unmanned aerial vehicle (UAV) as a test source. The micro UAV can perform an autonomous flight. Its absolute position is measured with a remote topographic instrument. By data processing, the received power pattern along the UAV flying path is reconstructed. The proposed setup has been validated on two standard wire antennas at 150 and 408 MHz with an estimated accuracy of 1 dB.

Positioning in indoor environment is one of the most important and interesting topic in navigation system that still present numerous open problems to investigate. Many researchers are attempting to investigate on technologies able to reach valid location in an indoor space, where the well-known GNSS positioning systems are not able to operate. Among the many solutions proposed for location-based services, several wireless communications technologies have the potential to be employed for indoor positioning. In this paper, an Ultrawideband (UWB) indoor positioning commercial system is presented which exploits two-way time of flight (TWTF) to compute range measurements. These measurements are used in multi-lateration method to compute the position of a trans-receiver (TAG). Firstly, the calibration results have been shown, comparing the internal IMU sensor of UWB system with a mass-market one, using the angles measured thanks to the total station as reference. Secondly, we also have statically analysed the positioning and the ranging capabilities of the system in a favourable environment, as an indoor office room. The average 3D accuracy obtained from the test is 100 ± 25mm. Also the ranging measurements has been analysed as the raw data from which the Pozyx® inner algorithm starts to compute the positions. It has been demonstrated that the range accuracy is about 320 ± 30mm. After these first tests, the system has also been tested in a harsh environment in a narrow corridor where a horizontal accuracy of about 87.4 mm is obtained with a maximum ranging error of ±225 mm. The system and algorithms tested in this report gave almost similar performances in both environments.

Italy is deeply afflicted by geo-hydrological risk, where a predominant part of its area is under risk.Recently, advanced research and sensors have played an important role in realizing automatic systems for landslide monitoring and to alerting. The cost of these systems, considering all parts, limits their use and the cost of each sensor influences the investment. Geodetic global navigation satellite system (GNSS) receivers, which are commonly used to realize these activities, are an appropriate example; however, their costs are quite high.The aim of this research was to test the actual performance of a mass-market GNSS receiver, with the purpose of verifying if such type of sensors can be used for landslide monitoring. In particular, the benefits due to the coupling between mass-market receivers and products offered by a network of GNSS permanent stations (e.g. Virtual RINEX) have been investigated.To verify the capability of these sensors to detect a deformation, under the minimum deformation detectable point of view, a special slide was built, in order to conduct a dedicated test. The support was moved both in horizontal and vertical directions with high precision, with purpose to detect correctly a three-dimensional movement.Tests were carried out considering the dependence of some factors: the most important are the acquisition time and the distance from the GNSS reference station. Interesting is the use of virtual reference station based on GNSS network, as a reference station: the performance achieved using Virtual RINEX for the control of movements and deformations are analysed. The accuracy and precision of movement determination were evaluated and compared, for each test, considering the different factors. The tests and results are described in this contribution.

Performing two independent surveys in 2016 and 2017 over a flat sample plot (6700 m ${}^2$ ), we compare snow-depth measurements from Unmanned-Aerial-System (UAS) photogrammetry and from a new high-resolution laser-scanning device (MultiStation) with manual probing, the standard technique used by operational services around the world. While previous comparisons already used laser scanners, we tested for the first time a MultiStation, which has a different measurement principle and is thus capable of millimetric accuracy. Both remote-sensing techniques measured point clouds with centimetric resolution, while we manually collected a relatively dense amount of manual data (135 pt in 2016 and 115 pt in 2017). UAS photogrammetry and the MultiStation showed repeatable, centimetric agreement in measuring the spatial distribution of seasonal, dense snowpack under optimal illumination and topographic conditions (maximum RMSE of 0.036 m between point clouds on snow). A large fraction of this difference could be due to simultaneous snowmelt, as the RMSE between UAS photogrammetry and the MultiStation on bare soil is equal to 0.02 m. The RMSE between UAS data and manual probing is in the order of 0.20–0.30 m, but decreases to 0.06–0.17 m when areas of potential outliers like vegetation or river beds are excluded. Compact and portable remote-sensing devices like UASs or a MultiStation can thus be successfully deployed during operational manual snow courses to capture spatial snapshots of snow-depth distribution with a repeatable, vertical centimetric accuracy.

We present a methodology to use a UAV (unmanned aerial vehicle) to perform photogrammetric surveys and detailed geological mapping in mountain areas. This work is specially related to the presented case study with the aim to realize geomorphological maps from UAVs, since they can house different types of sensors and acquire data more rapidly and cheaply than traditional geological surveys directly obtained with field observations. This work explains how UAVs can obtain digital terrain models, orthophotos and 3D models in order to create slope and aspect maps for geological purposes. By integrating data from UAVs with geological surveys made on the field, geological maps can be produced where many of the geological elements are presented. This paper presents the integration of geomatics and geological techniques. Starting from UAV slope map and orthophotos, a new geological map was created in a faster and more detailed way compared to traditional geological survey on the ground. The application of this method regards a sector of the Western Alps (NW Italy), formed by glaciers and deep-seated gravitational slope deformations.

The growth of location-based services (LBS) has increased rapidly in last years, mainly due to the possibility to exploit low-cost sensors installed in portable devices, such as smartphones and tablets. This work aims to show a low-cost multi-sensor platform developed by the authors in which an ultra-wideband (UWB) indoor positioning system is added to a classical global navigation satellite systems–inertial navigation system (GNSS-INS) integration, in order to acquire different synchronized data for further data fusion analysis in order to exploit seamless positioning. The data fusion is based on an extended Kalman filter (EKF) and on a geo-fencing approach which allows the navigation solution to be provided continuously. In particular, the proposed algorithm aims to solve a navigation task of a pedestrian user moving from an outdoor space to an indoor environment. The methodology and the system setup is presented with more details in the paper. The data acquired and the real-time positioning estimation are analysed in depth and compared with ground truth measurements. Particular attention is given to the UWB positioning system and its behaviour with respect to the environment. The proposed data fusion algorithm provides an overall horizontal and 3D accuracy of 35 cm and 45 cm, respectively, obtained considering 5 different measurement campaigns.