Increasing radiation power in half width microstrip leaky wave antenna by using slots technique

<p class="Default">The radiation power in the endfire is decreased while the main beam of half substrate integrated waveguide scan from broadside to endfire in a forward. The design of half-width microstrip leaky-wave antenna (HW-MLWA) has been presented in this work to increase the power radiation near endfire by using the slots technique in the radiation element. This slot leads to a decrease the cross-polarization. The proposed design comprises one element of HW-MLWA with repeated meandered square slots in the radiation element. One aspect of this antenna is generated by using a half substrate integrated waveguide with a full tapered feed line. The proposed antenna was terminated by load of 50 Ω, and feed on the other end of the antenna. Finally, the suggested design is simulated and acceptable results were found. The released gain is increased from 10.6 dBi to 12 dBi at 4.3 GHz. This design is suitable for unmanned aerial vehicle UAVs at C band application.</p>

Automatic Extraction of Damaged Houses by Earthquake Based on Improved YOLOv5: A Case Study in Yangbi

Efficiently and automatically acquiring information on earthquake damage through remote sensing has posed great challenges because the classical methods of detecting houses damaged by destructive earthquakes are often both time consuming and low in accuracy. A series of deep-learning-based techniques have been developed and recent studies have demonstrated their high intelligence for automatic target extraction for natural and remote sensing images. For the detection of small artificial targets, current studies show that You Only Look Once (YOLO) has a good performance in aerial and Unmanned Aerial Vehicle (UAV) images. However, less work has been conducted on the extraction of damaged houses. In this study, we propose a YOLOv5s-ViT-BiFPN-based neural network for the detection of rural houses. Specifically, to enhance the feature information of damaged houses from the global information of the feature map, we introduce the Vision Transformer into the feature extraction network. Furthermore, regarding the scale differences for damaged houses in UAV images due to the changes in flying height, we apply the Bi-Directional Feature Pyramid Network (BiFPN) for multi-scale feature fusion to aggregate features with different resolutions and test the model. We took the 2021 Yangbi earthquake with a surface wave magnitude (Ms) of 6.4 in Yunan, China, as an example; the results show that the proposed model presents a better performance, with the average precision (AP) being increased by 9.31% and 1.23% compared to YOLOv3 and YOLOv5s, respectively, and a detection speed of 80 FPS, which is 2.96 times faster than YOLOv3. In addition, the transferability test for five other areas showed that the average accuracy was 91.23% and the total processing time was 4 min, while 100 min were needed for professional visual interpreters. The experimental results demonstrate that the YOLOv5s-ViT-BiFPN model can automatically detect damaged rural houses due to destructive earthquakes in UAV images with a good performance in terms of accuracy and timeliness, as well as being robust and transferable.

How using aerial drones to deliver projects during Covid lockdown led to a 'new normal'

The paper illustrates how unmanned aerial vehicle surveys were used to support the designs for refurbishment of seven rural bridges in Wales during a Covid-19 lockdown in 2020. The hundreds of high-resolution photos captured for each structure were used to produce photo-realistic three-dimensional photogrammetry models using automated processes. Although born of necessity, the reduction in cost, duration and disruption together with the elimination of risks associated with conventional surveys show the case for wider adoption beyond the Covid-19 pandemic.

SYSTEM FOR PROVIDING AUTOMATIC NAVIGATION OF AN UNMANNED AERIAL VEHICLE IN THE VICINITY OF AN AIRFIELD

Рассмотрены вопросы разработки системы, способной обеспечивать автоматическую навигацию беспилотного летательного аппарата в окрестности аэродрома без использования дополнительных датчиков. Рассмотрен алгоритм решения этой задачи с использованием бортовой монокулярной системы технического зрения, функционирующей в диапазоне 1,55 мкм. Для обеспечения навигации беспилотный летательный аппарат оснащен системой информационного обмена, а в районе точки взлета-посадки в качестве наземных источников (маяков) предложено использовать полупроводниковые лазеры с некогерентным излучением длиной волны 1,55 мкм, которые обеспечивают работу системы в простых метеоусловиях. Путем измерений угла азимута в двух точках траектории движения беспилотного летательного аппарата вычисляются его координаты местоположения относительно взлетно-посадочной полосы, а также угол курса необходимый для выхода в начальную точку глиссады снижения. Ввиду того, что погрешности измерений обусловлены ошибками измерений угла азимута, курса и скорости полета, ошибками измерения временных интервалов в данной работе пренебрегаем. Полученные графики показывают, что погрешности измерения координат беспилотного летательного аппарата минимальны при пролете напротив маяка и резко возрастают при удалении от него, что обусловлено погрешностью измерения азимута и дальности. При этом измерение местоположения беспилотного летательного аппарата необходимо выполнять на минимальном удалении от маяка The article discusses the development of a system capable of providing automatic navigation of an unmanned aerial vehicle in the vicinity of an airfield without the use of additional sensors. We considered an algorithm for solving this problem using an onboard monocular vision system operating in the range of 1.55 microns. To ensure navigation, the unmanned aerial vehicle is equipped with an information exchange system, and in the area of the take-off and landing point, we propose to use semiconductor lasers with incoherent radiation with a wavelength of 1.55 microns, which ensure the operation of the system in simple weather conditions, as ground sources (beacons). By measuring the azimuth angle at two points of the trajectory of the unmanned aerial vehicle, we calculated its location coordinates relative to the runway, as well as the course angle necessary to reach the starting point of the descent glide path. Since measurement errors are caused by errors in measuring the azimuth angle, course and flight speed, we neglected errors in measuring time intervals in this work. The obtained graphs show that the errors in measuring the coordinates of an unmanned aerial vehicle are minimal when flying in front of the lighthouse and increase sharply when moving away from it, which is due to the error in measuring azimuth and range. At the same time, the measurement of the location of the unmanned aerial vehicle must be carried out at a minimum distance from the lighthouse

A Low-Cost and Ultralight Unmanned Aerial Vehicle-Borne Multicamera Imaging System Based on Smartphones

Newly developed oblique photogrammetry (OP) techniques based on unmanned aerial vehicles (UAVs) equipped with multicamera imaging systems are widely used in many fields. Smartphones cost less than the cameras commonly used in the existing UAV OP system, providing high-resolution images from a built-in imaging sensor. In this paper, we design and implement a novel low-cost and ultralight UAV OP system based on smartphones. Firstly, five digital cameras and their accessories detached from the smartphones are then fitted into a very small device to synchronously shoot images at five different perspective angles. An independent automatic capture control system is also developed to realize this function. The proposed smartphone-based multicamera imaging system is then mounted on a modified version of an existing lightweight UAV platform to form a UAV OP system. Three typical application examples are then considered to evaluate the performance of this system through practical experiments. Our results indicate that both horizontal and vertical location accuracy of the generated 3D models in all three test applications achieve centimeter-level accuracy with respect to different ground sampling distances (GSDs) of 1.2 cm, 2.3 cm, and 3.1 cm. The accuracy of the two types of vector maps derived from the corresponding 3D models also meet the requirements set by the surveying and mapping standards. The textural quality reflected by the 3D models and digital ortho maps (DOMs) are also distinguishable and clearly represent the actual color of different ground objects. Our experimental results confirm the quality and accuracy of our system. Although flight efficiency and the accuracy of our designed UAV OP system are lower than that of the commercial versions, it provides several unique features including very low-cost, ultralightweight, and significantly easier operation and maintenance.

Analytical RS-GBSM-Based Nonstationary Low-Altitude Air-to-Air Channel Modeling over Open Area

Aerial communication is very flexible due to almost no restrictions on geographical conditions. In recent years, with the development and application of the unmanned aerial vehicle, the air-to-air communication attracts dense interests from the researchers. More accurate and precise channel modeling for air-to-air communication is a new hot topic because of its essential role in the performance evaluation of the systems. This paper presents an analytical nonstationary regular-shaped geometry-based statistical model for low-altitude air-to-air communication over an open area with considerations on ground scattering. Analytical expressions of the channel impulse response and the autocorrelation functions based on the three-ray model are derived. Based on the assumption of uniform distribution of the ground scatterers, the distributions of the channel coefficients such as time delay and path attenuation are derived, simulated, compared, and fitted. The nonstationary characteristics of the channel are observed through the time-variant distributions of the channel coefficients as well as the time-variant autocorrelated functions and time-variant Doppler power spectrum density.

An Approach to Air-to-Surface Mission Planner on 3D Environments for an Unmanned Combat Aerial Vehicle

Recently, interest in mission autonomy related to Unmanned Combat Aerial Vehicles(UCAVs) for performing highly dangerous Air-to-Surface Missions(ASMs) has been increasing. Regarding autonomous mission planners, studies currently being conducted in this field have been mainly focused on creating a path from a macroscopic 2D environment to a dense target area or proposing a route for intercepting a target. For further improvement, this paper treats a mission planning algorithm on an ASM which can plan the path to the target dense area in consideration of threats spread in a 3D terrain environment while planning the shortest path to intercept multiple targets. To do so, ASMs are considered three sequential mission elements: ingress, intercept, and egress. The ingress and egress elements require a terrain flight path to penetrate deep into the enemy territory. Thus, the proposed terrain flight path planner generates a nap-of-the-earth path to avoid detection by enemy radar while avoiding enemy air defense threats. In the intercept element, the shortest intercept path planner based on the Dubins path concept combined with nonlinear programming is developed to minimize exposure time for survivability. Finally, the integrated ASM planner is applied to several mission scenarios and validated by simulations using a rotorcraft model.