Iran’s 12-Day War of Resistance: National Liberation as Self-Reliance

In recent years, Unmanned Aerial Vehicles (UAVs) have become very popular in civil and defense sectors. Due to their numerous applications, the UAV industry is flourishing with great pace. An autopilot having the complete flight control system is the heart of a UAV. It is an onboard system which controls and navigates the in-flight UAV autonomously. These days, multiple commercial solutions for UAV autopilot are available in the market. In these commercially off the shelf (COTS) solutions, mostly ailerons are used as the input control surface. PID (Proportional-integral-derivative) based heading controllers are generally used for steering the UAV in the desired direction. In our work, performance evaluation of two different heading-controllers is carried out. In both the schemes, aileron deflection acts as the input variable for the feedback and control mechanism. One of the controllers uses PID based controller while the other one makes use of phaselag based heading controller. First step in the controller design process includes selection of a nonlinear UAV model, which is linearized at steady state trim conditions. The next step includes design of linear PID and phase-lag controllers and their subsequent application on nonlinear model. Finally, the effectiveness of deigned controllers is gauged by comparing the simulation results of compensated linear and nonlinear models. Our investigation clearly proves that PID-based heading controllers are a better choice, as these have better transient and steady-state response as compared to Phase-lag controllers.

Since the 2nd World War and during the Cold War, the air defense radar has proven to be the main surveillance sensor, where each radar would cover a radius of more than 200 nautical miles. Apart from the electronic warfare, more recently the emergence of stealth or low observable technology, the evolution of ballistic and cruise missiles, as well as the democratization of UAVs (Unmanned Air Vehicles) or drones, have contested the capabilities of the typical surveillance radar. All these targets are difficult to detect, because they exhibit low RCS (Radar Cross Section), potentially flying at the upper or lower limits of the radar coverage or outside the expected velocity range (being either too slow, e.g. some UAVs, or too fast, like ballistic missiles). This chapter begins with the estimation of the RCS of various potential targets, as a function of the radar frequency band. In this way, the expected detection range against a set of targets can be calculated, for any given radar. Secondly, different radar types are taken into consideration, such as low frequency band radars or passive/multistatic radars, examining the respective advantages and disadvantages. Finally, some issues are discussed concerning the “kill chain” against difficult-to-detect targets, in an effort to defend efficiently the air space.

The article presents an analysis of the use of materials for the production of unmanned aerial vehicles (UAVs), developed using additive technologies (AT). The samples of materials mentioned in the article have the prospect of becoming advanced in modern UAVs production. The main factors that affect the properties of the printed material with the help of AT are also identified. Today, the production of materials for the manufacture of UAVs is developing rapidly, becoming more technological; production volumes are increasing, accuracy and quality of manufacturing parts are increasing with reduced costs. Additive technologies are ideal for the manufacture, printing, repair and modification of modern UAVs. Many parts for UAVs can be printed on a 3D printer. The use of AT is clearly demonstrated to optimize the production of UAV parts. In the case of the usual method of production of UAVs, their cost and complexity is quite high. The introduction of AT allows to significantly reduce the weight of the UAV components by reducing material costs. Studies have shown that the use of AT in the production of UAVs at the present stage will provide an opportunity to increase the aerodynamic characteristics of UAVs, reduce overall weight, and will allow the collection and repair of UAVs in the field. AT will also ensure the production of replacement parts that are needed in small volumes and that cannot be manufactured using traditional production technologies in the field. Thus, the introduction of AT will lead to a change in existing principles of design of printing technologies, the application of new approaches in the construction of modern 3D printers, the emergence of new, related to 3D printing technologies. That’s why the study of factors that affect the properties of the printed material of UAVs is highly relevant task and needs further research. Keywords: additive technologies, UAV, 3D printing.

Unmanned Aerial Vehicles (UAVs) are used in various applications, including crowd management, crime prevention, accident detection, and rescue operations. However, since UAVs perform their tasks independently, some UAV applications are dynamic and geographically distributed, which may require extensive real-time processing capabilities. Thus, processing UAV data locally can be challenging due to their limited computing capabilities. To overcome such limitations, fog and cloud computing can facilitate UAV application development by providing additional resource capacities when needed. Despite this, designing sophisticated and efficient UAV task offloading strategies that collaborate with fog and cloud technologies considering their service latency and energy consumption, is rarely addressed in the literature. Therefore, a collaborative offloading strategy for UAV applications is presented in this work, leveraging fog and cloud computing advantages and capabilities. This approach aims to minimize UAVs' service latency and energy consumption, as well as provide the required resources and services in real time. In addition, task offloading decisions are formulated using the Mixed-Integer Linear Programming (MILP) model to reduce the energy consumption of the entire UAV-fog-cloud system by optimizing the allocation of computation resources and communication requested by each UAV. The simulation results demonstrate that the proposed strategy can significantly reduce UAV service latency by 15.38%, 35.29%, and 59.26%, as well as decrease overall energy consumption (including processing and networking) by 3.3%, 7.37%, and 12% when compared to alternative standalone strategies (namely UAV, fog, and cloud). INDEX TERMS Unmanned aerial vehicle (UAV), cloud computing, fog computing, collaborative UAVs, energy-efficiency, task offloading. Unmanned Aerial Vehicles (UAVs) that have sensors, cameras, memory, and communication devices are becoming the most investigated emerging technologies in different fields, such as military, civilian, and industrial applications. Also, UAVs can play significant roles in many areas, such as providing logistic services, controlling, monitoring, and managing crowds, since they are commercially available and inexpensive. Moreover, UAVs can reduce operational costs and risks, and improve work efficiency (e.g., by reducing human interventions and reaching areas that are difficult to access using manned vehicles) [1] . However, UAVs that perform heavy tasks (e.g., image analysis and video recording) require high network traffic and produce more processing data. This leads to the requirement for more computational resources and communication support [2] . Also, processing UAV data locally is a challenging task due to their limited computing capabilities [3] . In this regard, some computing tasks can be offloaded from the UAVs and processed remotely on a cloud server, or fog nodes located at the edge of the networks [4] . Both cloud and fog computing are enabling technologies for operating and developing UAV applications, as well as providing additional resource capacity and network coverage for UAVs. Even though cloud computing is capable of providing efficient computing services, there will be significant communication delays when data is offloaded from local UAV devices to a remote cloud and retrieved data from

For a while, UAV (Unmanned Aerial Vehicles) use was limited to military applications, however recently UAVs are also used for a wide range of civilian applications. Some of the UAV applications may involve multiple UAVs that must cooperate to achieve a common task. This kind of applications is termed collaborative UAV applications. One of the main issues for multiple UAVs is developing an effective framework to enable the development of software systems for collaborative UAV operations. One possible approach is to rely on service-oriented computing and service-oriented middleware technologies to simplify the development and operations of such applications. This paper discusses the challenges of developing collaborative UAV applications and how the service-oriented middleware approach can help resolve some of these challenges. The paper also investigates the collaborative aspects of multiple UAVs and proposes a service-oriented middleware architecture that can satisfy the development and operations of such applications.

This article considers the use of an unmanned aerial vehicle (UAV) for covert video surveillance of a mobile target on the ground and presents a new online UAV trajectory planning technique with a balanced consideration of the energy efficiency, covertness, and aeronautic maneuverability of the UAV. Specifically, a new metric is designed to quantify the covertness of the UAV, based on which a multiobjective UAV trajectory planning problem is formulated to maximize the disguising performance and minimize the trajectory length of the UAV. A forward dynamic programming method is put forth to solve the problem online and plan the trajectory for the foreseeable future. In addition, the kinematic model of the UAV is considered in the planning process so that it can be tracked without any later adjustment. Extensive computer simulations are conducted to demonstrate the effectiveness of the proposed technique. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —The “Follow Me” flight mode is available in many unmanned aerial vehicle (UAV) products, and this technique enables a UAV to automatically follow a target. However, this flight mode may make the UAV noticeable to the target and compromise the video surveillance missions of the UAV. Inspired by some security surveillance applications where UAV surveillance is conducted so that a target would not take actions to avoid being monitored, we propose an efficient method to construct the trajectory for the UAV. The proposed method considers the visual covertness and the battery capacity limitation of the UAV, and it can produce a trajectory online for the UAV. The proposed method and scenario can potentially extend the “Follow Me” flight mode and generate new applications and market for UAVs.

Velocity controllers for a swarm of unmanned aerial vehicles

Unmanned Aerial Vehicles (UAVs) are used, in addition to the military, in various civilian applications. Some UAV applications may involve multiple UAVs working and collaborating together to achieve a common goal. Developing such applications is time and effort consuming due to the heterogeneity of UAVs and the complexity of the operations involved. These UAVs are usually monitored and controlled using peer-to-peer radio frequency communications. This requires either direct links between the UAVs and the ground station, or through multiple hops between them. This approach suffers from many limitations and it forces the user(s) to be at the mission location. In addition, it restricts the mission's area within the range of UAV communication. Overcome this issue, we propose a platform architecture that integrates the UAVs with the cloud computing paradigm, so that UAVs become as servers and part of the cloud. We modeled the UAVs in a Resources-Oriented Architecture (ROA); they provide their resources and services through the uniform interface RESTful HTTP. For distributed UAVs, we propose a broker architecture to separate the requester side from the provider side. The main purpose of this broker is to assign the requested tasks to the suitable available UAVs. The separation of responsibilities facilitates easier development of UAV applications on top of the platform.

&lt;span&gt;As a result of technological advances in robotic systems, electronic sensors, and communication techniques, the production of unmanned aerial vehicle (UAV) systems has become possible. Their easy installation and flexibility led these UAV systems to be used widely in both military and civilian applications. Note that the capability of one UAV is however limited. Nowadays, a multi-UAV system is of special interest due to the ability of its associate UAV members either to coordinate simultaneous coverage of large areas or to cooperate to achieve common goals/targets. This kind of cooperation/coordination requires a reliable communication network with a proper network model to ensure the exchange of both control and data packets among UAVs. Such network models should provide all-time connectivity to avoid dangerous failures or unintended consequences. Thus, the multi-UAV system relies on communication to operate. Flying ad hoc network (FANET) is moreover considered as a sophisticated type of wireless ad hoc network among UAVs which solved the communication problems into other network models. Along with the FANET’s unique features, challenges and open issues are also discussed especially in the routing protocols approach. We will try to present the expected transmission account metric with a new algorithm for reliability. In addition to this new algorithm mechanism, the metric takes into account the relative speed between UAVs, and thus the increase of the fluctuations in links between UAVs has been detected. Accordingly, the results show that the function of the AODV routing protocol with this metric becomes effective in high mobility environments.&lt;/span&gt;

With the recent advances in the aircraft technologies, software, sensors, and communications; unmanned aerial vehicles (UAVs) can offer a wide range of applications. Some of these applications may involve multiple UAVs that cooperate and collaborate to achieve a common goal. This kind of applications is termed collaborative UAVs applications. One of the main research topics for multiple UAVs is developing an effective framework to enable the development of software systems for collaborative UAVs operations. One possible approach is to rely on middleware technologies to simplify the development and operations of such applications. This paper discusses the challenges of developing collaborative UAVs applications and how middleware can help resolve some of these challenges. In addition, the paper studies the utilization of service-oriented middleware infrastructures for implementing and operating collaborative UAVs applications. Finally, the paper investigates the collaborative aspect of multiple UAVs and lists the functions needed for service-oriented middleware to satisfy the development and operations of such applications.

In the recent era, unmanned aerial vehicle (UAV) plays an important role in numerous application fields related to the wireless communication system. Due to its precise control, efficient deployment, and affordable cost, UAV-assisted communication attracts significant attention to all the sectors including the defense sector, agriculture sector, and security purpose, and so on. Though UAVassisted relaying has enormous advantages but there are potential challenges while UAV deploys as a relay. For example, deploying UAV in the wireless communication field, its battery life is the main concern due to its limited battery size and storage capacity. To get significant benefits from UAV while deployed in the cooperative communication network, the battery status of the UAV is an unavoidable issue. To minimize the aforementioned problem, energy harvesting (EH) techniques can be an efficient solution. The UAV can harvest energy from the transmitted power by the source and with the help of this harvested energy UAV can retransmit the signal to the destination. However, there are several parameters that also significantly influence the UAV-based cooperative system performance such as UAV’s position, time allocation factor and power allocation factor, and UAV’s height. Considering the importance of the aforementioned parameters, in this paper, we have considered simultaneous wireless information and power transfer (SWIPT) enabled UAV-assisted relaying network and evaluate the system outage performance with different parameters aspects. We have provided some insight about the parameters such as the UAV’s position, the power allocation factor and the time allocation factor and the UAV’s height by providing simulation results such as the outage probability versus transmit power in the different urban scenario, the outage probability versus time allocation factor and power allocation factor and the outage probability versus UAV’s height. These simulation results clearly show the significance of the abovementioned parameters in wireless-powered UAVassisted cooperative communication. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited.

Unmanned aerial vehicles (UAV) have been gaining momentum in recent years because of their vast application areas in the defence and civilian sectors. Their use can result in future missions to be more effective while also be conducted in a safer manner. UAVs, due to their large operational potential may be required to travel over long distances and prespecified way points thus requiring an effective and efficient decision making mechanism which allow the UAV to start and complete its mission. These missions may start and terminate at different or identical topological locations (or nodes). In the current paper a node-to-node graph theory energy costs modelling method is developed and presented. The modelling method requires as a priori the node-to-node energy costs. Furthermore, several propositions were presented to allow for the energy matrix to be perturbable, thus representing possible atmospheric variations which may occur during the UAVs mission. The UAV is modelled using energy graphs which allow a topological optimum to be obtained via suitable optimization algorithms. The energy costs implicitly contain time, propulsion force, and velocity information thus producing realistic results.

Increasing use of Unmanned Aerial Vehicles (UAVs) in civil and defense sectors, has led to increase in demands on UAV capabilities as well. Across several Department of Defense (DoD) agencies, such as Air Force, Navy, DARPA, and DARO, there has been a need for “multi-mission” capable UAVs that can achieve several objectives using a single platform. While conventional fixed-wing or rotary-wing platforms may be able to perform several missions, the ability to morph allows the vehicle to become truly efficient in meeting multiple objectives. Morphing aircraft have been studied for decades, however a truly biomimetic morphing capability with seamless aerodynamic transitions; remains elusive. Furthermore, the control of such vehicles that ensures stability during transitions, is still an active area of research. In this research, we have developed actuation mechanisms to achieve span extension, tip twist, sweep and anhedral/dihedral. These mechanisms were demonstrated in hardware, and initial free jet wind tunnel testing was also performed using a scaled prototype. The control of the aircraft undergoing large shape changes, also brings in the need for adaptive control, which was investigated in this study and a novel indirect adaptive control scheme, combining subspace system identification with optimal control was developed. We perform several studies using the control scheme and demonstrate applicability of the technique, as well as extensions to perform robust adaptive control; which becomes critical for the morphing aircraft application. These studies were performed in simulation in the current work, using models based on aerodynamic analysis of conventional and morphing wing mechanisms.

Civilian applications of Unmanned Aerial Vehicles (UAV) have rapidly been expanding recently. Thanks to military development many civil UAVs come via the defense sector. Although numerous UAVs can perform civilian tasks, the regulations imposed by FAA in the national airspace system and military equivalent agencies in restricted airspace need to be closely considered and followed in order to make progress in civilian applications. Personnel at the Jornada Experimental Range have developed approaches to abide by FAA and military regulations. Because of this, the enormous potential of UAVs for rangeland assessment, monitoring, and management is starting to be realized.

Hybrid unmanned aerial vehicles (UAVs) are gaining popularity in the defense sector. The introduction of a high-power electrical network provides new challenges in thermal management and safe vehicle operation. Existing efforts have focused on the modeling and control of thermal systems. However, the dynamic behavior of the electrical and mechanical components increases the complexity of the power management system. To enable model-based system design and real-time application tool development, this paper presents a graph-based modeling framework to represent the dynamic behavior of electrical and mechanical components onboard a UAV. An algorithm for composing a system-level graph model from component-level graph models is introduced. Cell and motor models are experimentally validated. A fault detection case is presented for a UAV model to demonstrate modeling capability for real-time applications.