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This paper presents a multipurpose UAV (unmanned aerial vehicle) for mountain rescue operations. The multi-rotors based flying platform and its embedded avionics are designed to meet environmental requirements for mountainous terrain such as low temperatures, high altitude and strong winds, assuring the capability of carrying different payloads (separately or together) such as: avalanche beacon (ARTVA) with automatic signal recognition and path following algorithms for the rapid location of snow-covered body; camera (visible and thermal) for search and rescue of missing persons on snow and in woods during the day or night; payload deployment to drop emergency kits or specific explosive cartridge for controlled avalanche detachment. The resulting small (less than 5 kg) UAV is capable of full autonomous flight (including take-off and landing) of a pre-programmed, or easily configurable, custom mission. Furthermore, the autopilot manages the sensors measurements (i.e. beacons or cameras) to update the flying mission automatically in flight. Specific functionalities such as terrain following were developed and implemented. Ground station programming of the UAV is not needed, except compulsory monitoring, as the rescue mission can be accomplished in a full automatic mode.

The use of unmanned aerial vehicle (UAV)-mounted radar for obtaining snowpack parameters has seen considerable advances over recent years. However, a robust method of snow density estimation still needs further development. The objective of this work is to develop a method to reliably and remotely estimate snow water equivalent (SWE) using UAV-mounted radar and to perform initial field experiments. In this paper, we present an improved scheme for measuring SWE using ultra-wide-band (UWB) (0.7 to 4.5 GHz) pseudo-noise radar on a moving UAV, which is based on airborne snow depth and density measurements from the same platform. The scheme involves autofocusing procedures with the frequency–wavenumber (F–K) migration algorithm combined with the Dix equation for layered media in addition to altitude correction of the flying platform. Initial results from field experiments show high repeatability (R > 0.92) for depth measurements up to 5.5 m, and good agreement with Monte Carlo simulations for the statistical spread of snow density estimates with standard deviation of 0.108 g/cm3. This paper also outlines needed system improvements to increase the accuracy of a snow density estimator based on an F–K migration technique.

Communication networks have to be resilient for quick reaction and recovery activities to be possible during catastrophes. Tethered Networked Flying Platforms (TNFPs) offer a viable way to lessen the effects of communication infrastructure failures in Beyond 5 G (B5G) networks. In this research, the best way to deploy TNFPs in disaster situations when conventional ground-based stations are jeopardized, including earthquakes and floods, is examined. In order to improve coverage and dependability, TNFPs, which include low-altitude platforms (LAPs), medium-altitude platforms (MAPs), and high altitude platforms (HAPs), operate at different altitudes. Optimizing power consumption, transmission distances, and coverage probability through adjustment of tether length and elevation angle are important deployment parameters. The simulation results show how efficient performance parameters, including line-of-sight probability, affect total coverage probability, Bit Error Rate (BER), and Signal-to-Noise Ratio (SNR). The results highlight TNFPs’ ability to guarantee robust communication networks in B5G environments.

The article presents the first implementation of the Signal Doppler Frequency (SDF) location method on an Unmanned Aerial Vehicle (UAV) named Autonomous System of Location radio EmmiteRs (ASLER), employing a DJI Matrice UAV as its mobile platform for the radio sensor. The system is used for position estimation, i.e., determining the location coordinates of localized radio emitters. Such functionality is the basis of radio reconnaissance, electronic warfare, or combat systems, and many radio navigation systems. The ASLER localization procedure is based on the Doppler localization method, also known as the SDF. Its distinctive feature is the use of a single moving platform for localization. In addition, the SDF allows simultaneous localization of multiple emission sources, which is an innovative distinction compared to other solutions of this class. ASLER is the first autonomous implementation of the SDF method on a flying platform. This paper illustrates the hardware and software implementation of location sensor, and results of the first empirical studies.

Terrain-aided navigation, which combines radar altitude with a digital terrain map (DTM), was developed before the era of the Global Positioning System to prevent error growth resulting from inertial navigation. Recently, cameras and substantial computational power have become ubiquitous in flying platforms, prompting interest in studying whether the radar altimeter can be replaced by a visual sensor.This paper presents a novel approach to vision-based terrain-aided localization by revisiting the correspondence and DTM (C-DTM) problem. We demonstrate that we can simplify the C-DTM problem by dividing it into a structure-from-motion (SFM) problem and then anchoring the solution to the terrain. The SFM problem can be solved using existing techniques such as feature detection, matching, and triangulation wrapped with a bundle adjustment algorithm. Anchoring is achieved by matching the point cloud to the terrain using ray-tracing and a variation of the iterative closest point method. One of the advantages of this two-step approach is that an innovative outlier filtering scheme can be included between the two stages to enhance overall robustness.The resulting algorithm consistently demonstrated high precision and statistical independence in the presence of initial errors across various simulations. The impact of different filtering methods was also studied, showing an improvement of 50% compared with the unfiltered case.The new algorithm has the potential to improve localization in real-world scenarios, making it a suitable candidate for pairing with an inertial navigation system and a Kalman f ilter to construct a comprehensive navigation system.

The paper proposes an ultra-wideband frequency selective rasorber (FSR) with low infrared emissivity for the composite detection threat of both radars and infrared sensors. Firstly, the equivalent circuit (EC) method based on transmission line (TL) theory is utilized to analyze the absorption/transmission conditions. Then, based on the analysis above, sinusoidal microstrip lines with non-frequency-varying characteristics are adopted in the design, which significantly enhances the transmission bandwidth of FSR. The FSR demonstrates an absorption band ranging from 2.65 GHz to 8.80 GHz and a transmission band ranging from 9.15 GHz to 17.71 GHz. Furthermore, an infrared shielding layer (IRSL) exhibiting low emissivity in the infrared band and high transmittance in the microwave band is applied to the FSR. The simulation and experiment results verify that the IRSL-FSR demonstrates an ultra-wide transmission band ranging from 9.16 GHz to 17.94 GHz and an ultra-wide absorption band ranging from 2.66 GHz to 8.01 GHz. Additionally, it exhibits a low emissivity value (0.23) in 8–14 μm, providing a viable solution to the formidable challenge of radar-infrared bistealth for satellites and other communication-enabled flying platforms.

The evolving requirements of next-generation mobile communications networks can be met by leveraging vertically deployed Unmanned Aerial Vehicle (UAV) platforms integrated with Free Space Optical communications (FSO). This integration offers a flexible and scalable architecture capable of delivering high-rate communication without requiring licenses while aligning with the multi-gigabit paradigm. In recent times, the increasing availability of commercial aerial platforms has facilitated experimental demonstrations of UAV-enabled FSO systems, which play a crucial role in proposed backhaul networks and point-to-point communications by overcoming Line-of-Sight (LOS) challenges. These systems can be rapidly deployed to meet sudden demand scenarios. This document provides a comprehensive review of relevant field demonstrations of UAV-enabled FSO relay systems, with a particular focus on commercially available, free-flying platforms that are driving advancements in this domain. It categorizes the different platforms by considering the operational altitudes of these systems and their payload actuation capacity, which determines their adaptability to variables. The analysis aims to distill the design considerations that lead to optimal performance regarding communications throughput and other relevant metrics. Moreover, it also attempts to highlight areas where design choices have fallen short, indicating gaps in current research efforts toward the widespread adoption of UAV-enabled FSO relay systems. Finally, this work endeavors to outline effective design considerations, guidelines, and recommendations to bridge these identified gaps. It serves as a valuable reference guide for researchers involved in developing UAV-enabled FSO relay systems, enabling them to make informed decisions and pave the way for the successful implementation of such systems.

Toroidal propellers, a new type of drone propellers capable of significantly reducing noise, offer new possibilities for future low-altitude flying platforms. In this study, a numerical model was established to analyze the aerodynamic noise of the toroidal propeller under normal atmospheric conditions. The aerodynamic calculations for the toroidal and benchmark propellers were performed to obtain noise source information using a transient large eddy simulation. The hybrid computational aeroacoustic method was employed to calculate the noise spectrum at different speeds and locations. Moreover, an experimental system for propellers was designed and built within an anechoic chamber to investigate the aerodynamic performance and noise characteristics at various speeds. The noise reduction effect of the toroidal propeller compared to the benchmark propeller was analyzed, taking into account the sound pressure level, lift coefficient, and figure of merit. At the same thrust level, the lift coefficient of the toroidal propeller increased by 187% relative to the benchmark propeller. The radial and axial sound pressure levels decreased by 5.2 dB(A) and 19.6 dB(A), respectively. The toroidal propeller significantly reduced noise while improving aerodynamic performance. This study provides a theoretical basis, experimental methods, and data support for the aerodynamic and noise calculations of toroidal propellers. It has significant engineering implications for the development of low-noise propellers for drones.

Authors aim to analyze the requirements for the use of simulation technologies for the Air Traffic Pilot License Theory and, based on the selected, measured, and interpreted parameters, to compare the platforms used by the Czech Air Force. At the University of Defence, the simulation center is used as a support instrument. The objective of this paper is to determine the most appropriate flying platform for student-pilots when employing basic radionavigation theory. To verify the analysis, simulated student flights were carried out. The first group of approaches was performed on the simulated platform of the Zlin Z142 aircraft, and the second group on the L39 Albatros aircraft. Individual flights were statistically evaluated and compared. The parameters for comparison were the deviation of the flight altitude compared to the recommended approach altitude and the deviation of the heading compared to the final approach course. Statistical evaluation of the performed simulated flights was made by F-test and verified confirmed that to teach the theoretical subject of Radionavigation, a slower-flying Zlin Z-142 is more suitable. According to the results, the Z142 platform gives the student more time to observe a pilotage error and correct it before starting the final approach phase.

Conlin, M.; Cohn, N., and Ruggiero, P., 2018. A quantitative comparison of low-cost Structure from Motion (SfM) data collection platforms on beaches and dunes. Observations of beach and dune geomorphology are critical for characterizing coastal processes and hazards. A relatively new approach for monitoring the coastline is Structure from Motion photogrammetry (SfM), a technique that uses overlapping photographs to reconstruct three-dimensional surfaces. In this study, a quantitative comparison of multiple low-cost kite-, pole-, and unmanned aerial vehicle (UAV)–based SfM data collection platforms is performed to illuminate important considerations when choosing an SfM platform for use in measuring beach and dune topography. A multicriteria analysis based on SfM results and platform usability is used to complete this comparison. Results show that UAV-based platforms received high performance scores, largely because these stable, high-flying platforms provide images with adequate texture to allow accurate three-dimensional topographic reconstruction. Although data extracted from the kite- and pole-based systems are less accurate, these platforms possess increased usability because of decreased barriers to entry and fewer environmental limitations (in the case of the pole), which increases their overall performance. These results illustrate that the overall effectiveness of a platform is based on many factors beyond vertical error of extracted data, and factors of platform usability can be important to consider when choosing an SfM platform. Furthermore, this multiplatform analysis reveals the important idea that different platforms can be optimal for different applications depending on the study site and environmental conditions. As the technology progresses, many improvements to platforms are likely to emerge, allowing SfM to become an even more useful tool for the coastal scientist.