Evaluating Global Navigation Satellite System (GNSS) Constellation Performance for Unmanned Aerial Vehicle (UAV) Navigation Precision

Accurate localization is paramount for unmanned aerial vehicles (UAVs) spanning various technical and industrial domains, necessitating a comprehensive assessment of global navigation satellite system (GNSS) precision. This study investigates the performance of distinct GNSS constellations in determining the precise location of a building utilizing a high-precision GNSS receiver. The receiver, incorporating advanced multi-frequency and full-constellation positioning capabilities, was integrated with a smartphone via Bluetooth to enable the UAV’s acquisition of centimeter-level positioning data. Sequential utilization of single satellite systems—such as GPS-only, GLONASS-only, Galileo-only, SBAS-only, and BeiDou-only—facilitated the documentation of latitude and longitude coordinates for the designated building. Subsequent comparison of these coordinates with a specialized Geographic Information System (GIS) was conducted to evaluate their positional accuracy. The comparative analysis underscores significant variability in the precision offered by each satellite constellation, providing valuable insights for optimizing UAV navigation across GIS, IoT, construction, and other sectors requiring high-precision localization. This research underscores the significance of high-precision GNSS receivers in enhancing UAV-based geospatial assessments, emphasizing the critical selection of appropriate satellite systems for tailored localization tasks. The study contributes to advancing UAV navigation strategies, ensuring robust and accurate geospatial data collection within diverse operational frameworks.

基于多密度流聚类的UAV-NOMA用户分簇与功率分配算法

针对无人机(Unmanned Aerial Vehicle,UAV)辅助非正交多址(Non-Orthogonal Multiple Access,NOMA)下行通信系统,提出了最大化和速率的用户动态分簇与功率分配方案.考虑用户服务质量与UAV位置约束,建立了和速率最大化的优化问题.由于目标函数的非凸性,将原问题解耦为三个子问题,分别优化UAV位置部署与用户连接、用户动态分簇、功率分配以提高系统性能.首先,基于K-means算法设计了UAV位置部署与用户连接方案,以减小路损为目的确定UAV最佳部署位置,同时选择其服务的最优用户群;其次,改进多密度流聚类(Multi-Density Stream Clustering, MDSC)算法,提出了单UAV下用户静态与动态分簇方案,静态分簇方案可自适应平衡簇数与簇用户数,并获得较大的簇内用户信道增益差异,动态分簇方案则针对用户移动属性,制定了即时更新策略;最后,使用分式规划(Fractional Programming,FP)二次变换的方法,引入辅助变量将原非凸问题变换为凸问题,交替优化辅助变量与功率分配因子,获得原非凸问题的次优解.仿真结果表明,与其他算法相比,本文分簇方案能获得更大的簇内信道差异与更小的簇内用户数标准差,同时用户系统性能也获得了显著提升.

基于DPBBO算法的智慧云仓UAV盘库作业优化

针对智慧云仓货物信息量大、易出现账物不符等库存管理问题,迫切需要将无人机(unmanned aerial vehicle, UAV)和工业物联网(industrial Internet of things, IIoT)集成起来,为仓储精细化管理提供解决方案。首先,分析盘库作业数据采集与信息交互运行机制,以危险避障和数据采集为约束函数,考虑了UAV在加速、减速、匀速、转角等飞行条件下的能耗差异,并以能耗最低和时间最短为目标函数构造UAV盘库作业数学模型;然后,设计了差分迁移-分段变异生物地理学优化(differential migration-piecewise mutation-biogeography-based optimization, DPBBO)算法对上述模型进行优化解算;最后,进行了仿真实验验证。结果表明:DPBBO算法对解决该盘库作业问题的效果较优,可以提升库存抽检任务的时效性和库存管理的准确性。

A new approach to study terrestrial yardang geomorphology based on high-resolution data acquired by unmanned aerial vehicles(UAVs): A showcase of whaleback yardangs in Qaidam Basin, NW China

Yardangs are wind-eroded ridges usually observed in arid regions on Earth and other planets. Previous geomorphology studies of terrestrial yardang fields depended on satellite data and limited fieldwork. The geometry measurements of those yardangs based on satellite data are limited to the length, the width, and the spacing between the yardangs; elevations could not be studied due to the relatively low resolution of the satellite acquired elevation data, e.g. digital elevation models(DEMs). However, the elevation information(e.g. heights of the yardang surfaces) and related information(e.g. slope) of the yardangs are critical to understanding the characteristics and evolution of these aeolian features. Here we report a novel approach, using unmanned aerial vehicles(UAVs) to generate centimeterresolution orthomosaics and DEMs for the study of whaleback yardangs in Qaidam Basin, NW China. The ultra-high-resolution data provide new insights into the geomorphology characteristics and evolution of the whaleback yardangs in Qaidam Basin. These centimeter-resolution datasets also have important potential in:(1) high accuracy estimation of erosion volume;(2) modeling in very fine scale of wind dynamics related to yardang formation;(3) detailed comparative planetary geomorphology study for Mars, Venus, and Titan.

Review of Effective Vegetation Mapping Using the UAV (Unmanned Aerial Vehicle) Method

We tried more precise mapping of vegetation using UAV?(unmanned aerial vehicle), as a new method of creating vegetation maps, and we?objected to be clearly the efficient mapping of vegetation using the UAV method by comparing vegetation maps created by analysing aerial photographs taken by a UAV and an aircraft (manned flight). The aerial photography using UAV was conducted in the Niida River estuary (the secondary river flowing into Minamisoma City in Fukushima Prefecture, Japan). The photography period was in August 2013. We analysed the aerial photographs using ArcGis 9 (Esri Japan Corporation, Tokyo, Japan). The aerial photographs of the main plant communities (Phragmites australis,?Typha domingensis, and?Miscanthus sacchariflorus) taken by the UAV could clearly discriminate each plant community at the 1/50 scale. Moreover, it could clearly discriminate the shape of a plant at the 1/10 scale. We compared the vegetation maps by analysing the aerial photos taken by a UAV (2013 shooting) and an aircraft (2011 shooting). As a result, the vegetation map created by the UAV method could clearly discriminate community distributions. We conclude that vegetation surveys using UAV are possible and are capable of a highly precise community division in places where field reconnaissance is difficult. The UAV method is effective and will contribute to the improvement of research methods in the future;this method may reduce research costs associated with a reduction in field survey days and man-power.

Received Power Based Unmanned Aerial Vehicles (UAVs) Jamming Detection and Nodes Classification Using Machine Learning

This paper presents a machine-learning method for detecting jamming UAVs and classifying nodes during jamming attacks onWireless Sensor Networks(WSNs).Jamming is a type of Denial of Service(DoS)attack and intentional interference where a malicious node transmits a high-power signal to increase noise on the receiver side to disrupt the communication channel and reduce performance significantly.To defend and prevent such attacks,the first step is to detect them.The current detection approaches use centralized techniques to detect jamming,where each node collects information and forwards it to the base station.As a result,overhead and communication costs increased.In this work,we present a jamming attack and classify nodes into different categories based on their location to the jammer by employing a single node observer.As a result,we introduced a machine learning model that uses distance ratios and power received as features to detect such attacks.Furthermore,we considered several types of jammers transmitting at different power levels to evaluate the proposed metrics using MATLAB.With a detection accuracy of 99.7%for the k-nearest neighbors(KNN)algorithm and average testing accuracy of 99.9%,the presented solution is capable of efficiently and accurately detecting jamming attacks in wireless sensor networks.

OFDM-UAV中继广播通信系统航迹优化方法

为了提高无人机中继广播通信系统的性能,针对频率选择性衰落信道,考虑基站到无人机以及无人机到用户的全通信链路,提出了基于正交频分复用(OFDM)技术的无人机中继广播通信系统航迹优化方法。首先提出了基于OFDM的无人机中继广播通信传输模型,对单用户节点中断概率和系统平均中断概率进行理论分析并给出近似计算公式;然后以平均中断概率最小化和最大用户中断概率最小化为优化准则,提出无人机的航迹优化方法并分析了各因素对系统中断性能的影响;最后通过计算机仿真,证明了所提航迹优化方法正确有效。研究表明:在多径信道下,基于OFDM的无人机中继广播通信系统能有效克服频率选择性衰落,且译码转发方式下的连通性优于放大转发方式;基于平均中断概率最小化准则得到的系统中断性能优于最大用户中断概率最小化准则。

A method to interpret fracture aperture of rock slope using adaptive shape and unmanned aerial vehicle multi-angle nap-of-the-object photogrammetry

The aperture of natural rock fractures significantly affects the deformation and strength properties of rock masses,as well as the hydrodynamic properties of fractured rock masses.The conventional measurement methods are inadequate for collecting data on high-steep rock slopes in complex mountainous regions.This study establishes a high-resolution three-dimensional model of a rock slope using unmanned aerial vehicle(UAV)multi-angle nap-of-the-object photogrammetry to obtain edge feature points of fractures.Fracture opening morphology is characterized using coordinate projection and transformation.Fracture central axis is determined using vertical measuring lines,allowing for the interpretation of aperture of adaptive fracture shape.The feasibility and reliability of the new method are verified at a construction site of a railway in southeast Tibet,China.The study shows that the fracture aperture has a significant interval effect and size effect.The optimal sampling length for fractures is approximately 0.5e1 m,and the optimal aperture interpretation results can be achieved when the measuring line spacing is 1%of the sampling length.Tensile fractures in the study area generally have larger apertures than shear fractures,and their tendency to increase with slope height is also greater than that of shear fractures.The aperture of tensile fractures is generally positively correlated with their trace length,while the correlation between the aperture of shear fractures and their trace length appears to be weak.Fractures of different orientations exhibit certain differences in their distribution of aperture,but generally follow the forms of normal,log-normal,and gamma distributions.This study provides essential data support for rock and slope stability evaluation,which is of significant practical importance.

High Spatial Resolution Mapping of Dykes Using Unmanned Aerial Vehicle(UAV) Photogrammetry: New Insights On Emplacement Processes

Remote sensing has played a pivotal role in our understanding of the geometry of dykes and dyke swarms on Earth,Venus and Mars(West and Ernst,1991;Mege and Masson,1995;Ernst et al.,2005).Since the 1970’s

面向UAV辅助的WSN信息年龄优化算法

提出了一种综合传感器能源供给、数据传输时效性和移动用户需求的系统平均信息年龄(AoI)优化算法。首先,采用无人机(UAV)辅助WSN来保障传感器的能量收集和数据传输。其次,引入AoI作为衡量指标,联合优化多设备调度、发射功率和UAV轨迹,建立了以最小化传感器的平均AoI为目标的非凸优化问题。然后,通过约束松弛、变量替换和连续凸逼近等方法,将非凸问题转化为凸问题,并设计了一种迭代式的平均AoI最小化算法。仿真结果表明:该算法在满足移动用户体验的同时有效提升了传感器数据新鲜度。

A landslide monitoring method using data from unmanned aerial vehicle and terrestrial laser scanning with insufficient and inaccurate ground control points

Non-contact remote sensing techniques,such as terrestrial laser scanning(TLS)and unmanned aerial vehicle(UAV)photogrammetry,have been globally applied for landslide monitoring in high and steep mountainous areas.These techniques acquire terrain data and enable ground deformation monitoring.However,practical application of these technologies still faces many difficulties due to complex terrain,limited access and dense vegetation.For instance,monitoring high and steep slopes can obstruct the TLS sightline,and the accuracy of the UAV model may be compromised by absence of ground control points(GCPs).This paper proposes a TLS-and UAV-based method for monitoring landslide deformation in high mountain valleys using traditional real-time kinematics(RTK)-based control points(RCPs),low-precision TLS-based control points(TCPs)and assumed control points(ACPs)to achieve high-precision surface deformation analysis under obstructed vision and impassable conditions.The effects of GCP accuracy,GCP quantity and automatic tie point(ATP)quantity on the accuracy of UAV modeling and surface deformation analysis were comprehensively analyzed.The results show that,the proposed method allows for the monitoring accuracy of landslides to exceed the accuracy of the GCPs themselves by adding additional low-accuracy GCPs.The proposed method was implemented for monitoring the Xinhua landslide in Baoxing County,China,and was validated against data from multiple sources.

Cooperative Anti-Jamming and Interference Mitigation for UAV Networks: A Local Altruistic Game Approach

To improve the anti-jamming and interference mitigation ability of the UAV-aided communication systems, this paper investigates the channel selection optimization problem in face of both internal mutual interference and external malicious jamming. A cooperative anti-jamming and interference mitigation method based on local altruistic is proposed to optimize UAVs’ channel selection. Specifically, a Stackelberg game is modeled to formulate the confrontation relationship between UAVs and the jammer. A local altruistic game is modeled with each UAV considering the utilities of both itself and other UAVs. A distributed cooperative anti-jamming and interference mitigation algorithm is proposed to obtain the Stackelberg equilibrium. Finally, the convergence of the proposed algorithm and the impact of the transmission power on the system loss value are analyzed, and the anti-jamming performance of the proposed algorithm can be improved by around 64% compared with the existing algorithms.

Cooperative UAV search strategy based on DMPC-AACO algorithm in restricted communication scenarios

Improvement of integrated battlefield situational awareness in complex environments involving dynamic factors such as restricted communications and electromagnetic interference(EMI)has become a contentious research problem.In certain mission environments,due to the impact of many interference sources on real-time communication or mission requirements such as the need to implement communication regulations,the mission stages are represented as a dynamic combination of several communication-available and communication-unavailable stages.Furthermore,the data interaction between unmanned aerial vehicles(UAVs)can only be performed in specific communication-available stages.Traditional cooperative search algorithms cannot handle such situations well.To solve this problem,this study constructed a distributed model predictive control(DMPC)architecture for a collaborative control of UAVs and used the Voronoi diagram generation method to re-plan the search areas of all UAVs in real time to avoid repetition of search areas and UAV collisions while improving the search efficiency and safety factor.An attention mechanism ant-colony optimization(AACO)algorithm is proposed for UAV search-control decision planning.The search strategy is adaptively updated by introducing an attention mechanism for regular instruction information,a priori information,and emergent information of the mission to satisfy different search expectations to the maximum extent.Simulation results show that the proposed algorithm achieves better search performance than traditional algorithms in restricted communication constraint scenarios.

IRS Assisted UAV Communications against Proactive Eavesdropping in Mobile Edge Computing Networks

In this paper,we consider mobile edge computing(MEC)networks against proactive eavesdropping.To maximize the transmission rate,IRS assisted UAV communications are applied.We take the joint design of the trajectory of UAV,the transmitting beamforming of users,and the phase shift matrix of IRS.The original problem is strong non-convex and difficult to solve.We first propose two basic modes of the proactive eavesdropper,and obtain the closed-form solution for the boundary conditions of the two modes.Then we transform the original problem into an equivalent one and propose an alternating optimization(AO)based method to obtain a local optimal solution.The convergence of the algorithm is illustrated by numerical results.Further,we propose a zero forcing(ZF)based method as sub-optimal solution,and the simulation section shows that the proposed two schemes could obtain better performance compared with traditional schemes.

Determination of Arctic melt pond fraction and sea ice roughness from Unmanned Aerial Vehicle (UAV) imagery

Melt ponds on Arctic sea ice are of great significance in the study of the heat balance in the ocean mixed layer, mass and salt balances of Arctic sea ice, and other aspects of the earth-atmosphere system. During the 7th Chinese National Arctic Research Expedition, aerial photographs were taken from an Unmanned Aerial Vehicle over an ice floe in the Canada Basin. Using threshold discrimination and three-dimensional modeling, we estimated a melt pond fraction of 1.63% and a regionally averaged surface roughness of 0.12 for the study area. In view- of the particularly foggy environment of the Arctic, aerial images were defogged using an improved dark channel prior based image defog algorithm, especially adapted for the special conditions of sea ice images. An aerial photo mosaic was generated, melt ponds were identified from the mosaic image and melt pond fractions were calculated. Three-dimensional modeling techniques were used to generate a digital elevation model allowing relative elevation and roughness of the sea ice surface to be estimated. Analysis of the relationship between the distributions of melt ponds and sea ice surface roughness show-s that melt ponds are smaller on sea ice with higher surface roughness, while broader melt ponds usually occur in areas where sea ice surface roughness is lower.

A Realistic 3D Non-Stationary Channel Model for UAV-to-Vehicle Communications Incorporating Fuselage Posture

Considering the unmanned aerial vehicle(UAV) three-dimensional(3D) posture, a novel 3D non-stationary geometry-based stochastic model(GBSM) is proposed for multiple-input multipleoutput(MIMO) UAV-to-vehicle(U2V) channels. It consists of a line-of-sight(Lo S) and non-line-of-sight(NLo S) components. The factor of fuselage posture is considered by introducing a time-variant 3D posture matrix. Some important statistical properties, i.e.the temporal autocorrelation function(ACF) and spatial cross correlation function(CCF), are derived and investigated. Simulation results show that the fuselage posture has significant impact on the U2V channel characteristic and aggravate the non-stationarity. The agreements between analytical, simulated, and measured results verify the correctness of proposed model and derivations. Moreover, it is demonstrated that the proposed model is also compatible to the existing GBSM without considering fuselage posture.

一种基于IRS和UAV辅助通信系统分析

为提升智能反射面(IRS)和无人机(UAV)辅助混合通信系统的数据传输速率,提出一种优化用户速率方案。该方案考虑了全双工UAV(FD-UAV)辅助传输模式,IRS辅助传输模式和IRS、FD-UAV辅助混合传输模式(IRS-FD-UAV)。建立联合IRS被动波束形成相位(PBP)和UAV/IRS位置的最大化用户速率的目标问题。考虑目标问题的非凸性,利用块坐标下降法(BCD)将原目标问题分解成2个子问题,分别利用黎曼共轭梯度法和交替求解法求解。性能分析表明,相比于FD-UAV和IRS辅助传输模式,IRS-FD-UAV辅助传输模式具有较高的传输速率。

Road boundary estimation to improve vehicle detection and tracking in UAV video

Video processing is one challenge in collecting vehicle trajectories from unmanned aerial vehicle(UAV) and road boundary estimation is one way to improve the video processing algorithms. However, current methods do not work well for low volume road, which is not well-marked and with noises such as vehicle tracks. A fusion-based method termed Dempster-Shafer-based road detection(DSRD) is proposed to address this issue. This method detects road boundary by combining multiple information sources using Dempster-Shafer theory(DST). In order to test the performance of the proposed method, two field experiments were conducted, one of which was on a highway partially covered by snow and another was on a dense traffic highway. The results show that DSRD is robust and accurate, whose detection rates are 100% and 99.8% compared with manual detection results. Then, DSRD is adopted to improve UAV video processing algorithm, and the vehicle detection and tracking rate are improved by 2.7% and 5.5%,respectively. Also, the computation time has decreased by 5% and 8.3% for two experiments, respectively.

Communication Resource-Efficient Vehicle Platooning Control With Various Spacing Policies

Platooning represents one of the key features that connected automated vehicles may possess as it allows multiple automated vehicles to be maneuvered cooperatively with small headways on roads. However, a critical challenge in accomplishing automated vehicle platoons is to deal with the effects of intermittent and sporadic vehicle-to-vehicle data transmissions caused by limited wireless communication resources. This paper addresses the co-design problem of dynamic event-triggered communication scheduling and cooperative adaptive cruise control for a convoy of automated vehicles with diverse spacing policies. The central aim is to achieve automated vehicle platooning under various gap references with desired platoon stability and spacing performance requirements, while simultaneously improving communication efficiency. Toward this aim, a dynamic event-triggered scheduling mechanism is developed such that the intervehicle data transmissions are scheduled dynamically and efficiently over time. Then, a tractable co-design criterion on the existence of both the admissible event-driven cooperative adaptive cruise control law and the desired scheduling mechanism is derived. Finally, comparative simulation results are presented to substantiate the effectiveness and merits of the obtained results.

通信约束下UAV集群协同拦截任务分配算法

针对多无人机协同拦截多机动目标的任务分配问题,同时考虑到真实战场环境中存在的通信约束以及探测范围约束条件,本文提出了分步一致性拍卖算法(SCBAA)。首先,对真实战场环境中存在的通信约束以及探测范围约束等问题进行了描述分析,构建了多无人机协同拦截任务分配模型,设计了综合效能函数以及相应约束条件。其次,为解决多无人机协同打击单一目标的不平衡任务分配以及冲突消解问题,将原任务分配过程分为主要任务分配以及次要任务分配两部分,通过多次拍卖以及冲突消解实现多无人机对单一目标的任务分配。仿真结果表明,该算法可有效解决通信约束条件下的分布式多无人机协同拦截问题,并适应动态环境中任务分配对实时性的要求。