A Survey of Air-to-Ground Propagation Channel Modeling for Unmanned Aerial Vehicles

In recent years, there has been a dramatic increase in the use of unmanned aerial vehicles (UAVs), particularly for small UAVs, due to their affordable prices, ease of availability, and ease of operability. Existing and future applications of UAVs include remote surveillance and monitoring, relief operations, package delivery, and communication backhaul infrastructure. Additionally, UAVs are envisioned as an important component of 5G wireless technology and beyond. The unique application scenarios for UAVs necessitate accurate air-to-ground (AG) propagation channel models for designing and evaluating UAV communication links for control/non-payload as well as payload data transmissions. These AG propagation models have not been investigated in detail when compared to terrestrial propagation models. In this paper, a comprehensive survey is provided on available AG channel measurement campaigns, large and small scale fading channel models, their limitations, and future research directions for UAV communication scenarios

Development of Return to Base Flight Trajectory Generator Based on Dubins Path - Vector Field Method

In a Return to Base (RTB) situation, aircraft needs to immediately fly back to its origin airport. Since there is no published flight procedure for an RTB, an Air Traffic Controller (ATC) will assist the pilot for the flight procedure to fly. The objective of this work is to generate a flight trajectory in RTB situation based on the available airport flight procedures (departure and arrival) in Kertajati airport. The Dubins Path was used as a method to generate the flight trajectory and supported by the Vector-Field Methodology. The Python programming simulation was used to simulate the flight trajectory generation in the normal condition, second closest waypoint condition, and different parameters value condition. The trajectory was simulated based on flight characteristic of a single engine aircraft (Cesna 172) and multi-engine aircrafts (Boeing 737-800NG). The simulation results show that the Dubins Path and Vector-Field methodology success to generate the flight trajectory in different types of condition and parameters. The increase in aircraft velocity and the decrease in aircraft bank angle caused an increase in the aircraft turning radius. While, the decrease in aircraft flight path angle caused increase in the length of Dubins Path line

A Fuzzy Guidance System for Rendezvous and Pursuit of Moving Targets

This article presents the development of a fuzzy guidance system (FGS) for unmanned aerial vehicles capable of pursuing and performing rendezvous with static and mobile targets. The system is designed to allow the vehicle to approach a maneuvering target from a desired direction of arrival and to terminate the rendezvous at a constant distance from the target. In order to perform a rendezvous with a maneuvering target, the desired direction of arrival is adjusted over time to always approach the target from behind, so that the aircraft and target velocity vectors become aligned. The proposed guidance system assumes the presence of an autopilot and uses a set of Takagi–Sugeno fuzzy controllers to generate the orientation and speed references for the velocity and heading control loops, given the relative position and velocity between the aircraft and the target. The FGS treats the target as a mobile waypoint in a 4-D space (position in 2-dimensions, desired crossing heading and speed) and guides the aircraft on suitable trajectories towards the target. Only when the vehicle is close enough to the rendezvous point, the guidance law is complemented with an additional linear controller to manage the terminal formation keeping phase. The capabilities of the proposed rendezvous-FGS are verified in simulation on both maneuvering and non-maneuvering targets. Finally, experimental results using a multi-rotor aerial system are presented for both fixed and accelerating targets

CNS+A capabilities for the integration of unmanned aircraft in controlled airspace

In this paper, the system requirements for the integration of Remotely Piloted Aircraft Systems (RPAS) in controlled airspace regions are discussed. The specificities in terms of Air Traffic Management (ATM) level of service, jurisdiction for deconfliction duties and prevalent traffic characteristics are analysed to support the identification of operational and equipage requirements for RPAS developers. Communication, Navigation, Surveillance, ATM and Avionics (CNS+A) equipment play an essential role in airspace regions characteried by high levels of Air Traffic Services (ATS) and a higher probability of traffic conflicts. A denser route structure and a more frequent occurrence of traffic conflicts mandate high CNS performance, as the deconfliction by ATM crucially relies on accurate and reliable CNS information. Notwithstanding, the reduced jurisdiction of aircraft in deconfliction duties also offers an opportunity to RPAS developers, as it relieves the requirements for on-board expert processing

Unmanned Aerial Vehicle (UAV) mission planning based on Fast Marching Square (FM²) planner and Differential Evolution (DE)

Nowadays, mission planning for Unmanned Aerial Vehicles (UAVs) is a very attractive research field. UAVs have been a research focus for many purposes. In military and civil fields, the UAVs are very used for different missions. Many of these studies require a path planning to perform autonomous flights. Several problems related to the physical limitations of the UAV arise when the planning is carried out, as well as the maintenance of a fixed flight level with respect to the ground to capture videos or overlying images. This work presents an approach to plan missions for UAVs keeping a fixed flight level constraint. An approach is proposed to solve these problems and to generate effective paths in terms of smoothness and safety distance in two different types of environments: 1) 3D urban environments and 2) open field with non-uniform terrain environments. Many proposed activities to be carried out by UAVs in whatever the environment require a control over the altitude for different purposes: energy saving and minimization of costs are some of these objectives. In general terms, the planning is required to avoid all obstacles encountered in the environment and to maintain a fixed flight level during the path execution. For this reason, a mission planning requires robust planning methods. The method used in this work as planner is the Fast Marching Square (FM2) method, which generates a path free of obstacles. As a novelty, the method proposed includes two adjustment parameters. Depending on the values of these parameters, the restriction of flight level can be modified, as well as the smoothness and safety margins from the obstacles of the generated paths. The Dubins airplane model is used to check if the path resulting from the FM2 is feasible according to the constraints of the UAV: its turning rate, climb rate and cruise speed. Besides, this research also presents a novel approach for missions of Coverage Path Planning (CPP) carried out by UAVs in 3D environments. These missions are focused on path planning to cover a certain area in an environment in order to carry out tracking, search or rescue tasks. The methodology followed uses an optimization process based on the Differential Evolution (DE) algorithm in combination with the FM2 planner. Finally, the UAVs formation problem is introduced and addressed in a first stage using the planner proposed in this thesis. A wide variety of simulated experiments have been carried out to illustrate the efficiency and robustness of the approaches presented, obtaining successful results in different urban and open field 3D environments.Hoy en día la planificación de misiones para vehículos aéreos no tripulados (UAV) es un campo de investigación muy atractivo. Los UAV son foco de investigación en numerosas aplicaciones, tanto en el campo civil como militar. Muchas de estas aplicaciones requieren de un sistema de planificación de ruta que permita realizar vuelos autónomos y afrontar problemas relacionados con las limitaciones físicas del UAV y con requerimientos como el nivel de vuelo sobre el suelo para, entre otras funciones, poder capturar videos o imágenes. Este trabajo presenta una propuesta de planificador para vehículos aéreos no tripulados que permite resolver los problemas citados previamente, incluyendo en la planificación las consideraciones cinemáticas del UAV y las restricciones de nivel de vuelo, generando rutas suaves, realizables y suficientemente seguras para dos tipos diferentes de entornos 3D: 1) entornos urbanos y 2) campos abiertos con terrenos no uniformes. El método utilizado en esta tesis como base para la planificación es el método Fast Marching Square (FM2), que genera un camino libre de obstáculos. Como novedad, el método propuesto incluye dos parámetros de ajuste. Dependiendo de los valores de estos parámetros, se puede modificar la restricción de nivel de vuelo, así como la suavidad y los márgenes de seguridad respecto a los obstáculos de las rutas generadas. El modelo cinemático de Dubins se utiliza para verificar si la ruta resultante de nuestro planificador es realizable de acuerdo con las restricciones del UAV: su velocidad de giro, velocidad de ascenso y velocidad de crucero. Además, esta tesis también presenta una propuesta novedosa para la planificación de misiones de Coverage Path Planning (CPP) en entornos 3D. Estas misiones se centran en la planificación de rutas para cubrir un área determinada de un entorno con el fin de llevar a cabo tareas de rastreo, búsqueda o rescate. La metodología seguida utiliza un proceso de optimización basado en el algoritmo Differential Evolution (DE) en combinación con nuestro planificador FM2. Como parte final de la tesis, el problema de formación de UAVs se introduce y aborda en una primera etapa utilizando el planificador FM2 propuesto.Programa Oficial de Doctorado en Ingeniería Eléctrica, Electrónica y AutomáticaPresidente: Antonio Giménez Fernández.- Secretario: Luis Santiago Garrido Bullón.- Vocal: Raúl Suárez Feijó

Routing Unmanned Vehicles in GPS-Denied Environments

Most of the routing algorithms for unmanned vehicles, that arise in data gathering and monitoring applications in the literature, rely on the Global Positioning System (GPS) information for localization. However, disruption of GPS signals either intentionally or unintentionally could potentially render these algorithms not applicable. In this article, we present a novel method to address this difficulty by combining methods from cooperative localization and routing. In particular, the article formulates a fundamental combinatorial optimization problem to plan routes for an unmanned vehicle in a GPS-restricted environment while enabling localization for the vehicle. We also develop algorithms to compute optimal paths for the vehicle using the proposed formulation. Extensive simulation results are also presented to corroborate the effectiveness and performance of the proposed formulation and algorithms.Comment: Publised in International Conference on Umanned Aerial System

Rapid Trajectory Prediction for a Fixed-Wing UAS in a Uniform Wind Field with Specified Arrival Times

This paper presents an algorithm to rapidly generate trajectories for a kinematic fixed-wing Unmanned Aircraft System (UAS) model flying at constant altitude in a uniform wind field. Arrival times are specified by operators and rapid generation is accomplished via an elliptic integral problem formulation. Simulations are provided that illustrate this approach in the context of NASA's UAS Traffic Management Project

Unmanned Aircraft System Navigation in the Urban Environment: A Systems Analysis

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140665/1/1.I010280.pd

Surveillance Using Multiple Unmanned Aerial Vehicles

This study examines the performance and limitations of a heuristic cooperative control (CC) surveillance algorithm for multiple unmanned aerial vehicles (UAVs) under both simulation and demonstration. The algorithm generates Dubin\u27s based paths and provides velocity feedback to accomplish simultaneous arrival onto a surveillance orbit around the target and maintains position while orbiting. The CC algorithm has two modes: one that generates commands to multiple UAVs for simultaneous arrival to a surveillance orbit, and one that maintains equal angular spacing about the orbit. In addition to positional performance metrics, percentage of target in-view time was also measured based on the UAV\u27s side camera field of view (FOV). Simulation tested both modes under wind conditions of 0%, 10%, 25%, and 50% of the nominal airspeed (Vnom). Results showed that the algorithm maintained UAV position with winds 25% of Vnom, but instabilities appeared at 50% where large overshoots appeared on the downwind side of the orbit. Target visibility was most impacted by crosstrack errors that steadily grew with increasing winds. Roll of the UAV showed the greatest impact on the FOV due to its coupling effect with crosstrack error. Overall target in-view time also improved with increasing numbers of UAVs for all wind conditions