A novel framework to intercept GPS-denied,bomb-carrying,nonmilitary,kamikaze drones:Towards protecting critical infrastructures

Protection of urban critical infrastructures(CIs)from GPS-denied,bomb-carrying kamikaze drones(G-BKDs)is very challenging.Previous approaches based on drone jamming,spoofing,communication interruption and hijacking cannot be applied in the case under examination,since G-B-KDs are uncontrolled.On the other hand,drone capturing schemes and electromagnetic pulse(EMP)weapons seem to be effective.However,again,existing approaches present various limitations,while most of them do not examine the case of G-B-KDs.This paper,focuses on the aforementioned under-researched field,where the G-B-KD is confronted by two defensive drones.The first neutralizes and captures the kamikaze drone,while the second captures the bomb.Both defensive drones are equipped with a net-gun and an innovative algorithm,which,among others,estimates the locations of interception,using a real-world trajectory model.Additionally,one of the defensive drones is also equipped with an EMP weapon to damage the electronics equipment of the kamikaze drone and reduce the capturing time and the overall risk.Extensive simulated experiments and comparisons to state-of-art methods,reveal the advantages and limitations of the proposed approach.More specifically,compared to state-of-art,the proposed approach improves:(a)time to neutralize the target by at least 6.89%,(b)maximum number of missions by at least 1.27%and(c)total cost by at least 5.15%.

DroneRFa:用于侦测低空无人机的大规模无人机射频信号数据集

为研究与发展反无人机检测识别技术,该文公开了一个名为DroneRFa的大规模无人机射频信号数据集。该数据集使用软件无线电设备探测无人机与遥控器相互通信的射频信号,包含城市户外场景下运动无人机信号9类、城市室内场景下信号15类以及背景参照信号1类。每类数据有不少于12个片段,每个片段包含1亿个以上的采样点。数据采集覆盖了3个ISM无线电频段,记录无人机多频通信的真实活动。该数据集具有详细的无人机户外飞行距离和工作频段标注,以前缀字符结合二进制编码的形式方便用户灵活访问所需数据。此外,该文提供了基于频谱可视统计特征和基于深度学习表征的两种无人机识别方案,以验证数据集的可靠和有效性。

Classification of birds and drones by exploiting periodical motions in Doppler spectrum series

With the rapidly growing abuse of drones, monitoring and classification of birds and drones have become a crucial safety issue. With similar low radar cross sections(RCSs), velocities, and heights, drones are usually difficult to be distinguished from birds in radar measurements. In this paper, we propose to exploit different periodical motions of birds and drones from highresolution Doppler spectrum sequences(DSSs) for classification.This paper presents an elaborate feature vector representing the periodic fluctuations of RCS and micro kinematics. Fed by the Doppler spectrum and feature sequence, the long to short-time memory(LSTM) is used to solve the time series classification.Different classification schemes to exploit the Doppler spectrum series are validated and compared by extensive real-data experiments, which confirms the effectiveness and superiorities of the proposed algorithm.

Using Improved Particle Swarm Optimization Algorithm for Location Problem of Drone Logistics Hub

Drone logistics is a novel method of distribution that will become prevalent.The advantageous location of the logistics hub enables quicker customer deliveries and lower fuel consumption,resulting in cost savings for the company’s transportation operations.Logistics firms must discern the ideal location for establishing a logistics hub,which is challenging due to the simplicity of existing models and the intricate delivery factors.To simulate the drone logistics environment,this study presents a new mathematical model.The model not only retains the aspects of the current models,but also considers the degree of transportation difficulty from the logistics hub to the village,the capacity of drones for transportation,and the distribution of logistics hub locations.Moreover,this paper proposes an improved particle swarm optimization(PSO)algorithm which is a diversity-based hybrid PSO(DHPSO)algorithm to solve this model.In DHPSO,the Gaussian random walk can enhance global search in the model space,while the bubble-net attacking strategy can speed convergence.Besides,Archimedes spiral strategy is employed to overcome the local optima trap in the model and improve the exploitation of the algorithm.DHPSO maintains a balance between exploration and exploitation while better defining the distribution of logistics hub locations Numerical experiments show that the newly proposed model always achieves better locations than the current model.Comparing DHPSO with other state-of-the-art intelligent algorithms,the efficiency of the scheme can be improved by 42.58%.This means that logistics companies can reduce distribution costs and consumers can enjoy a more enjoyable shopping experience by using DHPSO’s location selection.All the results show the location of the drone logistics hub is solved by DHPSO effectively.

基于Raspberry Pi及Drone Kit的无人机飞行控制教学实践应用

基于开源硬件Raspberry Pi,Pixhawk及开源软件Drone Kit,设计了高校无人机飞行控制教学实践课程。课程中使用Raspberry Pi作为无人机的机载计算机与Pixhawk飞控芯片协同工作,通过使用MAVLink协议通信。学生在实践操作中需要掌握硬件各接口的功能属性进行无人机组装,在调测环境下,基于Drone Kit开发无人机飞行控制程序。所提的实践课程可以提高学生的动手实践能力,新环境下的创新应用能力能加深对飞行控制技术的理论理解。

A Shuffling-Steganography Algorithm to Protect Data of Drone Applications

In Saudi Arabia,drones are increasingly used in different sensitive domains like military,health,and agriculture to name a few.Typically,drone cameras capture aerial images of objects and convert them into crucial data,alongside collecting data from distributed sensors supplemented by location data.The interception of the data sent from the drone to the station can lead to substantial threats.To address this issue,highly confidential protection methods must be employed.This paper introduces a novel steganography approach called the Shuffling Steganography Approach(SSA).SSA encompasses five fundamental stages and three proposed algorithms,designed to enhance security through strategic encryption and data hiding techniques.Notably,this method introduces advanced resistance to brute force attacks by employing predefined patterns across a wide array of images,complicating unauthorized access.The initial stage involves encryption,dividing,and disassembling the encrypted data.A small portion of the encrypted data is concealed within the text(Algorithm 1)in the third stage.Subsequently,the parts are merged and mixed(Algorithm 2),and finally,the composed text is hidden within an image(Algorithm 3).Through meticulous investigation and comparative analysis with existing methodologies,the proposed approach demonstrates superiority across various pertinent criteria,including robustness,secret message size capacity,resistance to multiple attacks,and multilingual support.

HQNN-SFOP:Hybrid Quantum Neural Networks with Signal Feature Overlay Projection for Drone Detection Using Radar Return Signals-A Simulation

With the wide application of drone technology,there is an increasing demand for the detection of radar return signals from drones.Existing detection methods mainly rely on time-frequency domain feature extraction and classical machine learning algorithms for image recognition.This method suffers from the problem of large dimensionality of image features,which leads to large input data size and noise affecting learning.Therefore,this paper proposes to extract signal time-domain statistical features for radar return signals from drones and reduce the feature dimension from 512×4 to 16 dimensions.However,the downscaled feature data makes the accuracy of traditional machine learning algorithms decrease,so we propose a new hybrid quantum neural network with signal feature overlay projection(HQNN-SFOP),which reduces the dimensionality of the signal by extracting the statistical features in the time domain of the signal,introduces the signal feature overlay projection to enhance the expression ability of quantum computation on the signal features,and introduces the quantum circuits to improve the neural network’s ability to obtain the inline relationship of features,thus improving the accuracy and migration generalization ability of drone detection.In order to validate the effectiveness of the proposed method,we experimented with the method using the MM model that combines the real parameters of five commercial drones and random drones parameters to generate data to simulate a realistic environment.The results show that the method based on statistical features in the time domain of the signal is able to extract features at smaller scales and obtain higher accuracy on a dataset with an SNR of 10 dB.On the time-domain feature data set,HQNNSFOP obtains the highest accuracy compared to other conventional methods.In addition,HQNN-SFOP has good migration generalization ability on five commercial drones and random drones data at different SNR conditions.Our method verifies the feasibility and effectiveness of signal detection methods based on quantum computation and experimentally demonstrates that the advantages of quantum computation for information processing are still valid in the field of signal processing,it provides a highly efficient method for the drone detection using radar return signals.

Drone Usage in Civil Engineering—A Case Study of the Pristina-Gjilan Highway

The use of drones in construction engineering has gained increasing attention in recent years due to its potential to revolutionize the industry. Drones, offer the ability to capture high-resolution aerial imagery and collect data that was previously difficult or impossible to obtain. The integration drones in construction engineering presents opportunities for accurate data collection, analysis and visualization, which can improve decision-making processes and improve project outcomes. For example, drones equipped with GIS technology can be used to capture high-resolution aerial images of construction sites, allowing engineers to monitor progress, identify potential issues, and make informed adjustments as needed. By harnessing drones, civil engineers in the civil engineering field can potentially optimize project planning, design and execution while minimizing risks and costs. The work of this topic examines the case of the use of Drones combined with GIS in construction engineering. During this study, aerial photography of a certain segment of the Pristina-Gjilan Highway was taken. The results generated by the processing of aerial photos have been compared with the project. However, further research is needed to fully understand the capabilities and limitations of these technologies in this specific context, as well as to explore any potential challenges and barriers to their widespread adoption.

Multi-agent Based Hierarchy Simulation Models of Carrier-based Aircraft Catapult Launch

With the aid of multi-agent based modeling approach to complex systems, the hierarchy simulation models of carrier-based aircraft catapult launch are developed. Ocean, carrier, aircraft, and atmosphere are treated as aggregation agents, the detailed components like catapult, landing gears, and disturbances are considered as meta-agents, which belong to their aggregation agent. Thus, the model with two layers is formed i.e. the aggregation agent layer and the meta-agent layer. The information communication among all agents is described. The meta-agents within one aggregation agent communicate with each other directly by information sharing, but the meta-agents, which belong to different aggregation agents exchange their information through the aggregation layer first, and then perceive it from the sharing environment, that is the aggregation agent. Thus, not only the hierarchy model is built, but also the environment perceived by each agent is specified. Meanwhile, the problem of balancing the independency of agent and the resource consumption brought by real-time communication within multi-agent system （MAS） is resolved. Each agent involved in carrier-based aircraft catapult launch is depicted, with considering the interaction within disturbed atmospheric environment and multiple motion bodies including carrier, aircraft, and landing gears. The models of reactive agents among them are derived based on tensors, and the perceived messages and inner frameworks of each agent are characterized. Finally, some results of a simulation instance are given. The simulation and modeling of dynamic system based on multi-agent system is of benefit to express physical concepts and logical hierarchy clearly and precisely. The system model can easily draw in kinds of other agents to achieve a precise simulation of more complex system. This modeling technique makes the complex integral dynamic equations of multibodies decompose into parallel operations of single agent, and it is convenient to expand, maintain, and reuse the program codes.

基于YOLOX-drone的反无人机系统抗遮挡目标检测算法

为解决现实场景下无人机目标被部分遮挡,导致不易检测问题,本文提出了基于YOLOX-S改进的反无人机系统目标检测算法YOLOX-drone.首先,建立无人机图像数据集;其次,搭建YOLOX-S目标检测网络,在此基础上引入坐标注意力机制,来增强无人机的目标图像显著度,突出有用特征抑制无用特征;然后,再去除特征融合层中自下而上的路径增强结构,减少网络复杂度,并设计了自适应特征融合网络结构,增强有用特征的表达能力,抑制干扰,提升检测精度.在DUT-AntiUAV数据集上的测试结果表明:YOLOX-drone与YOLOX-S、YOLOv5-S和YOLOX-tiny相比,平均准确率(IoU=0.5)提升了3.2%、4.7%和10.1%;在自建的无人机图像数据集上的测试结果表明:YOLOX-drone与原YOLOX-S目标检测模型相比,在无遮挡、一般遮挡、严重遮挡情况下,平均准确率(IoU=0.5)分别提高了2.4%、2.1%和6.4%,验证了改进的算法具有良好的抗遮挡检测能力.

Modeling of Carrier-based Aircraft Ski Jump Take-off Based on Tensor

A general mathematical model of carrier-based aircraft ski jump take-off is derived based on tensor. The carrier, the aircraft body and the movable parts of the landing gears are treated as independent entities. These entities are assembled into a multi-rigid-body system with flexible links. Dynamical equations of each entity are derived on the basis of the Newton law and the Euler transformation. Using the invariance property of the tensor, the dynamical and kinematical equations are converted to tensor forms which are invariant under time-dependent coordinate transformations. Then the tensor-formed equations are expressed by the matrix operation. Differential equation group of the matrix form is formulated for the programming. The closure of the model is discussed, and the simulation results are given.

Guidance and Control Techniques of Carrier-Based Aircraft for Automatic Carrier Landing

We summarize the guidance and control techniques of automatic carrier landing for carrier-based aircraft.First,we analyze the carrier landing operations of the manned fixed-wing aircraft,unmanned fixed-wing aircraft and helicopters.Second,we look into the navigation and guidance system and the flight control methods for current different aircraft.Finally,we draw several conclusions of the development prospects for aircraft carrier landing,including the precision landing control techniques,precision approach and landing guidance techniques,and adaptive,reconfigurable and intelligent flight control techniques.

Parameter Optimization of Nose Landing Gear Considering Both Take-off and Landing Performance of Catapult Take-off Carrier-Based Aircraft

Optimization of the parameters of landing gear systems with double-stage air springs of catapult take-off carrier-based aircraft is here studied based on the mathematical equations of the classic dual mass spring-damper dynamic model.Certain standards for both take-off and landing performance are put forward.The contradictory factors between take-off and landing processes are analyzed.The optimization of oil in the pin area and the area near the rear oil hole is performed.Then these optimized parameters are used to assess the influence of the initial pressure of the low chamber,the ratio of the high chamber to the low chamber,and the tire inflation pressure on the performance of arresting landing and catapult take-off.The influences of these parameters on carrier-based aircraft and the aircraft-carrier on aircraft catapult take-off is also assessed.Based on the results of the simulation,respective take-off criteria must be drafted considering different types of aircraft and different take-off load cases,all of which must be matched to parameters relevant to catapult take-off.

Dynamics Analysis of Carrier-Based Aircraft with Off-Center Catapult Launch

In order to enhance the safety of the catapult launch of the carrier-based aircraft,the catapult launch multibody dynamic model is established aiming at the problem of off center catapult launch.The whole catapult process including four stages which are buffering,tensioning,releasing and taxiing is taken into consideration and the body dynamics of the off-center catapult during each stage is analyzed.The catapult launch dynamic differences between the conditions only considering taxiing and that considering four stages are compared,and the effects of the different initial off center distances considering four stages on the attitude,landing gear load and acceleration of the carrier based aircraft during catapult launch are discussed.The results show that only considering taxiing may underestimate the dynamics of the carrier-based aircraft substantially.When taking four stages into consideration,the initial off-center distance has small influence on the aircraft dynamic characteristics during buffering and tensioning but has larger influence on that during releasing and taxiing.The increase of the off-center distance will cause the enhancement of the aircraft rolling and yawing,which may lead to the load difference between the left and right landing gears and the increase of the aircraft lateral acceleration.The establishment and simulation of the catapult launch multi body dynamic model founded on buffering,tensioning,releasing and taxiing provide reference for the carrier-based aircraft design and analysis of the catapult launch dynamics.

Detection and Classification on Amateur Drones Based on Cepstrum of Radio Frequency Signal

As a prospective component of the future air transportation system,unmanned aerial vehicles(UAVs)have attracted enormous interest in both academia and industry.However,small UAVs are barely supervised in the current situation.Crash accidents or illegal airspace invading caused by these small drones affect public security negatively.To solve this security problem,we use the back-propagation neural network(BPNN),the support-vector machine(SVM),and the k-nearest neighbors(KNN)method to detect and classify the non-cooperative drones at the edge of the flight restriction zone based on the cepstrum of the radio frequency(RF)signal of the drone’s downlink.The signal from five various amateur drones and ambient wireless devices are sampled in an electromagnetic clean environment.The detection and classification algorithm based on the cepstrum properties is conducted.Results of the outdoor experiments suggest the proposed workflow and methods are sufficient to detect non-cooperative drones with an average accuracy of around 90%.The mainstream downlink protocols of amateur drones can be classified effectively as well.

The Use of Drones in Forestry

Recently, drones have found applicability in a variety of study fields, one of these being forestry, where an increasing interest is given to this segment of technology, especially due to the high-resolution data that can be collected flexibly in a short time and at a relatively low price. Also, drones have an important role in filling the gaps of common data collected using manned aircraft or satellite remote sensing, while having many advantages both in research and in various practical applications particularly in forestry as well as in land use in general. This paper aims to briefly describe the different approaches of applications of UAVs （Unmanned Aircraft Vehicles） in forestry, such as forest mapping, forest management planning, canopy height model creation or mapping forest gaps. These approaches have great potential in the near future applications and their quick implementation in a variety of situations is desirable for the sustainable management of forests.

A Drones Optimal Path Planning Based on Swarm Intelligence Algorithms

The smart city comprises various interlinked elements which communicate data and offers urban life to citizen.Unmanned Aerial Vehicles(UAV)or drones were commonly employed in different application areas like agriculture,logistics,and surveillance.For improving the drone flying safety and quality of services,a significant solution is for designing the Internet of Drones(IoD)where the drones are utilized to gather data and people communicate to the drones of a specific flying region using the mobile devices is for constructing the Internet-of-Drones,where the drones were utilized for collecting the data,and communicate with others.In addition,the SIRSS-CIoD technique derives a tuna swarm algorithm-based clustering(TSA-C)technique to choose cluster heads(CHs)and organize clusters in IoV networks.Besides,the SIRSS-CIoD technique involves the design of a biogeography-based optimization(BBO)technique to an optimum route selection(RS)process.The design of clustering and routing techniques for IoD networks in smart cities shows the novelty of the study.A wide range of experimental analyses is carried out and the comparative study highlighted the improved performance of the SIRSS-CIoD technique over the other approaches.

DYNAMIC RESPONSE ANALYSIS OF CARRIER-BASED AIRCRAFT DURING LANDING

In view of the complexity of landing on the deck of aircraft carrier,a systematic model,composed of sixdegree-of-freedom mathematic model of carrier-based aircraft,four-degree-of-freedom model of landing gears and six-degree-of-freedom mathematic model of carrier,is established in the Matlab-Simulink environment,with damping function of landing gears and dynamic characteristics of tires being considered.The model,where the carrier movement is introduced,is applicable for any abnormal landing condition.Moreover,the equations of motion and relevant parameter are also derived.The dynamic response of aircraft is calculated via the variable step-size RungeKuta algorithm.The effect of attitude angles of aircraft and carrier movement during the process of landing is illustrated in details.The analytical results can provide some reference for carrier-based aircraft design and maintenance.

A mobility compensation method for drones in SG-eloT

In order to achieve the specific goal of a smart grid,the concept of electricity Internet of Things(eloT)has been proposed to assist the monitoring and inspection of power transmission line state and optimize the asset utilization.The long power transmission line and the complex field operation environment urge the introduction of drones into the eloT for fast power transmission line inspection,data collection from sensors for further big data analysis,adaptive control of power line voltage,etc.Additionally,drones can also act as a central communication control or relay point to serve the data exchange among sensors,drones and power transmission line maintenance personnel in the scenario where the conventional mobile communication service is not available.However,the fast mobility of drones may affect the signal transmission and position estimation performance,which may further deteriorate the networking performance.In order to solve this problem,a mobility compensation method is proposed,which includes the steps of frequency offset estimation and relative velocity calculation.Through the Monte Carlo simulations,the proposed algorithm shows favorable gains compared with the conventional ones.

Optimal Preview Control for Automatic Carrier Landing System of Carrier-Based Aircraft with Air Wake

Carrier-based aircraft carrier landing is a special kind of tracking control problem and not suitable for classical control methods,which may miss the desired performance or result in overdesign.Therefore,we present an optimal preview control for automatic carrier landing system(ACLS)by using state information of system,as well as future reference information,which can avoid the shortcomings of classical control methods.Since the flight performance of carrier-based aircraft is disturbed by air wake when the aircraft flies near the area of carrier stern,we design a disturbance rejection strategy to ensure that aircraft track the glide path with high precision and robustness.Further,carrier-based aircraft is a complex nonlinear system.However,the nonlinear model of carrier-based aircraft can be linearized at equilibrium landing state and decoupled into the longitudinal model and the lateral model.Therefore,an optimal preview control system is designed.The simulation results of a carrier-based aircraft show that the optimal preview control system can effectively suppress air wake.Tracking accuracy of optimal preview controller is higher than that of the proportional integral differential(PID)control system.