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.

Unmanned aerial vehicle based intelligent triage system in mass-casualty incidents using 5G and artificial intelligence

BACKGROUND:Rapid on-site triage is critical after mass-casualty incidents(MCIs)and other mass injury events.Unmanned aerial vehicles(UAVs)have been used in MCIs to search and rescue wounded individuals,but they mainly depend on the UAV operator’s experience.We used UAVs and artificial intelligence(AI)to provide a new technique for the triage of MCIs and more efficient solutions for emergency rescue.METHODS:This was a preliminary experimental study.We developed an intelligent triage system based on two AI algorithms,namely OpenPose and YOLO.Volunteers were recruited to simulate the MCI scene and triage,combined with UAV and Fifth Generation(5G)Mobile Communication Technology real-time transmission technique,to achieve triage in the simulated MCI scene.RESULTS:Seven postures were designed and recognized to achieve brief but meaningful triage in MCIs.Eight volunteers participated in the MCI simulation scenario.The results of simulation scenarios showed that the proposed method was feasible in tasks of triage for MCIs.CONCLUSION:The proposed technique may provide an alternative technique for the triage of MCIs and is an innovative method in emergency rescue.

Seamless integration of above-and undercanopy unmanned aerial vehicle laser scanning for forest investigation

Background:Current automated forest investigation is facing a dilemma over how to achieve high tree-and plotlevel completeness while maintaining a high cost and labor efficiency.This study tackles the challenge by exploring a new concept that enables an efficient fusion of aerial and terrestrial perspectives for digitizing and characterizing individual trees in forests through an Unmanned Aerial Vehicle(UAV)that flies above and under canopies in a single operation.The advantage of such concept is that the aerial perspective from the above-canopy UAV and the terrestrial perspective from the under-canopy UAV can be seamlessly integrated in one flight,thus grants the access to simultaneous high completeness,high efficiency,and low cost.Results:In the experiment,an approximately 0.5 ha forest was covered in ca.10 min from takeoff to landing.The GNSS-IMU based positioning supports a geometric accuracy of the produced point cloud that is equivalent to that of the mobile mapping systems,which leads to a 2–4 cm RMSE of the diameter at the breast height estimates,and a 4–7 cm RMSE of the stem curve estimates.Conclusions:Results of the experiment suggested that the integrated flight is capable of combining the high completeness of upper canopies from the above-canopy perspective and the high completeness of stems from the terrestrial perspective.Thus,it is a solution to combine the advantages of the terrestrial static,the mobile,and the above-canopy UAV observations,which is a promising step forward to achieve a fully autonomous in situ forest inventory.Future studies should be aimed to further improve the platform positioning,and to automatize the UAV operation.

Unmanned Aerial Vehicle Control of Major Sugarcane Diseases and Pests in Low Latitude Plateau

This research was aimed at the defects in traditional artificial spraying control method and the problems such as the difficulty in pesticides applying,labor shortage and low operating efficiency in the middle and late stage of sugarcane high stalk crops.The aerial pesticide application technology for sugarcane main diseases and pests was systematically developed and demonstrated from the aspects of aircraft type choice,selection of special pesticides and auxiliaries,integration of pesticides and equipment,field operation,technical specifications,and large-scale application organization mode.The UAV model and flight technical parameters suitable for the sugarcane planting area in low-latitude plateau were analyzed,and the optimal agent formulation combination and application technology of the UAV flight control were screened out,and the UAV flight control was applied to the major sugarcane pests and diseases control in the low-latitude plateau in large scale(UAV flight control was popularized and applied to 15 527 hm 2 in 2018).The research results provided mature whole-process technical support for the normalization of the application of the UVA flight control of major sugarcane pests and diseases.The UAV control technology for major sugarcane pests and diseases had the advantages of ultra-low pesticides applying dosage and high operating efficiency,and could effectively solve the problems such as the difficulty in pesticides applying,labor shortage and low operating efficiency in the middle late growth stage of high stalk crops.This technology successfully opened up a simple,efficient and new way for the effective control of major sugarcane pests and diseases,and practically accelerated the process of integrated control and prevention of sugarcane pests and diseases.In addition,this technology had an extremely significant effect on reducing the loss of sugarcane farmers and enterprises caused by the epidemic and outbreak of sugarcane pests and diseases,increasing sugarcane yield and sugar content.At the same time,this technology played an important role in realizing the whole-process precise control of sugarcane pests and diseases,improving the quality and increasing the efficiency of sugarcane,and guaranteeing the national sugar safety.

Research on Vegetation Coverage Status of Urban-rural Fringe in Guizhou Using Unmanned Aerial Vehicle

Unmanned aerial vehicle technology was used to survey the vegetation coverage of typical urban-rural fringe, and descriptive statistics and geostatistical methods were used to analyze the urban-rural fringe of spatial heterogeneity of vegetation coverage. The results showed that vegetation coverage in the study area was 27.2176% with the coefficient of variation of 31.7786%; that the vegetation coverage in separation distance of 〈0.18＇ showed positive spatial correlation, and the spatial correlation of vegetation coverage in separation distance of 〈0.18＇ was greater than that in 〉0.18＇; that the best fitting model for Semivariance function was exponential model with spatial variation ratio 0.726, which showed strong spatial correlation, and the spatial correlated scale was 0.18＇; that the vegetation coverage data in the study area was relatively stable, and the instability mainly occurred on the border of the study area and the surroundings.

Detection of UAV Target Based on Continuous Radon Transform and Matched Filtering Process for Passive Bistatic Radar

Long-time integration technique is an effective way of improving target detection performance for unmanned aerial vehicle(UAV)in the passive bistatic radar(PBR),while range migration(RM)and Doppler frequency migration(DFM)may have a major effect due to the target maneuverability.This paper proposed an innovative long-time coherent integration approach,regarded as Continuous Radon-matched filtering process(CRMFP),for low-observable UAV target in passive bistatic radar.It not only mitigates the RM by collaborative research in range and velocity dimensions but also compensates the DFM and ensures the coherent integration through the matched filtering process(MFP).Numerical and real-life data following detailed analysis verify that the proposed method can overcome the Doppler mismatch influence and acquire comparable detection performance.

Joint waveform selection and power allocation algorithm in manned/unmanned aerial vehicle hybrid swarm based on chance-constraint programming

In this paper, we propose a joint waveform selection and power allocation(JWSPA) strategy based on chance-constraint programming(CCP) for manned/unmanned aerial vehicle hybrid swarm(M/UAVHS) tracking a single target. Accordingly,the low probability of intercept(LPI) performance of system can be improved by collaboratively optimizing transmit power and waveform. For target radar cross section(RCS) prediction, we design a random RCS prediction model based on electromagnetic simulation(ES) of target. For waveform selection, we build a waveform library to adaptively manage the frequency modulation slope and pulse width of radar waveform. For power allocation,the CCP is employed to balance tracking accuracy and power resource. The Bayesian Cramér-Rao lower bound(BCRLB) is adopted as a criterion to measure target tracking accuracy. The hybrid intelli gent algorithms, in which the stochastic simulation is integrated into the genetic algorithm(GA), are used to solve the stochastic optimization problem. Simulation results demonstrate that the proposed JWSPA strategy can save more transmit power than the traditional fixed waveform scheme under the same target tracking accuracy.

Contour Based Path Planning with B-Spline Trajectory Generation for Unmanned Aerial Vehicles (UAVs) over Hostile Terrain

This research focuses on trajectory generation algorithms that take into account the stealthiness of autonomous UAVs;generating stealthy paths through a region laden with enemy radars. The algorithm is employed to estimate the risk cost of the navigational space and generate an optimized path based on the user-specified threshold altitude value. Thus the generated path is represented with a set of low-radar risk waypoints being the coordinates of its control points. The radar-aware path planner is then approximated using cubic B-splines by considering the least radar risk to the destination. Simulated results are presented, illustrating the potential benefits of such algorithms.

面向外辐射源雷达发射站定位的合作无人机航迹规划方法研究

在广域未知环境中,外辐射源雷达机动部署常面临难以及时获取第三方发射站精确位置信息的难题。为此,该文提出一种基于合作无人机航迹规划的发射站定位方法。首先,利用单个无人机作为合作目标,建立2维场景下的定位模型和量测方程,并采用列文伯格-马夸尔特(Levenberg-Marquardt, LM)算法进行解算。然后,构建融合Fisher信息和控制参数约束的优化函数,对无人机航迹进行动态规划,从而提高发射站定位的精度和方法的实用性。最后,仿真实验表明,在最大控制距离约束下,所提方法的定位结果优于直线航迹和经典优化航迹,最终发射站定位精度小于双基距离差量测标准差,能够满足外辐射源雷达系统目标探测定位的应用要求。

基于杂波拖尾分布的雷达无人机检测性能分析

固定翼无人机(unmanned aerial vehicle,UAV)给雷达低空监视提出了严峻挑战。分析雷达对固定翼UAV的检测性能,可为雷达UAV检测能力评估和技术升级提供重要参考。本文结合雷达探测低空固定翼UAV外场实测数据,首先分析了低空固定翼UAV雷达接收信号幅度统计分布,采用多项式对杂波拖尾导致的虚警概率进行拟合建模;然后,根据虚警概率分布得到雷达检测门限;进而根据UAV回波+杂波幅度分布理论推导得到雷达检测概率;最后,将理论分析性能与传统性能分析结果、雷达实际检测性能进行对比。结果表明,采用多项式对杂波拖尾导致的虚警概率进行单独建模,由此获得的雷达检测门限精度更高,从而使雷达UAV检测性能分析结果较传统性能分析结果更准确。

不同海况条件下舰载无人机着舰安全分析

针对无人机上舰的使用需求,本文对舰载无人机着舰开展了系统的研究。建立了机-舰-环境综合模型和舰载无人机全自动着舰引导控制系统;基于建立的舰载无人机着舰综合模型对不同海况下的着舰过程进行仿真分析,研究不同海况条件以及航母不同航速和遭遇角对着舰安全的影响。仿真研究表明:在复杂海况下,航母可通过适当提高航速以获得更高的着舰成功率,但过高的航速会导致舰尾流扰动加剧,使得着舰成功率显著下降;通过对仿真结果进行统计分析,给出了不同海况下的着舰安全范围,为无人机着舰辅助决策提供参考。

基于微型激光雷达的无人机智能化电力线路巡检技术研究

介绍了一种利用激光探测和测距(LiDAR)进行实时电力线检测的算法,并且对微型激光雷达无人机进行电力线路巡检抽象建模。通过使用平面分析法对巡检现场进行距离的比较来分割点云,并提取一组电力线候选点,这些点被拟合到线段上,线段根据它们的共线性质进一步分组比较。该方法可利用图像的共线特性完成特征检验,并在光线条件差以及线路背景复杂的环境下仍可获得较为可靠的巡检结果。案例中电力线路垂直平均误差最大为0.49 m,其他所有直线的估计平均误差都小于0.07 m,水平拟合时,所有平均误差都在0.14 m以内。验证了所提出基于微型激光雷达的无人机技术进行电力线路智能化巡检方法的有效性与可行性。

基于遗传算法的无人机载穿墙三维SAR航迹规划方法

传统手持或车载穿墙雷达由于架设高度受限,无法对城市高层建筑内部目标进行透视成像,无人机载穿墙雷达具有灵活机动、高效便捷、无高度限制等优势,可对城市高层楼宇进行大范围三维穿透探测。三维层析合成孔径雷达(SAR)成像广泛采用多基线扫描模式,以获得高度向高分辨能力,但存在高度向空域欠采样导致的栅瓣问题。对此,该文提出一种基于遗传算法的无人机载穿墙三维SAR航迹规划方法,通过非均匀化飞行航迹,削弱周期性的雷达回波能量叠加,从而抑制栅瓣、实现更优的成像质量。该算法结合飞行距离与无人机载穿墙雷达成像质量的内在关系,建立了无人机航迹规划代价函数;利用遗传算法对3种典型的无人机飞行轨迹关键控制点进行基因编码,并进行基因杂交、变异等以优化种群与个体;最终通过最小化代价函数,分别筛选出3种典型飞行模式下的最优飞行航迹。仿真和实测数据的三维成像结果表明:相较于传统等间距多基线飞行模式,所提方法显著抑制了成像目标的栅瓣效应;此外,无人机斜线飞行的航迹长度明显缩短,提高了无人机载穿墙SAR成像效率。

人工等离子体云团与无人机群的散射研究

电离层中释放的金属蒸气产生人工等离子体云团,其可显著改变无线电波传播。本文利用几何绕射理论(geometrical theory of diffraction, GTD)和有限元法(finite element method, FEM)相结合的方法,给出了经由天线、人工等离子云团和无人机(unmanned aerial vehicle, UAV)群组成的传播链路中信号强度计算方法。利用30~70 MHz甚高频(very high frequency, VHF)信号研究人工等离子体云团与UAV群的复合散射特性,得出如下结论:接收功率随着信号频率增加呈下降趋势;当机群由N架UAV构成时,阵因子迭加使机群雷达散射截面(radar cross section, RCS)出现一定的起伏,同相迭加时,接收功率可比单个UAV高约20lg N dB;利用人工等离子体云团散射可实现VHF频段用于对米级尺度RCS目标进行超视距探测,有助于解决紧急情况下电离层扰动对高频探测的不利影响。

阿尔金地区“天空地深”一体化找矿勘查评价体系应用实践——以阿亚克-瓦石峡南为例

阿尔金地区属中高山地形,地势陡峭,海拔一般在2 000 m以上,比高大于300 m。高山区切割较深,地表基本无植被,基岩裸露较好。长期以来,因极端恶劣的交通条件,矿产勘查开发受到严重制约。新一轮找矿突破行动主攻昆仑-阿尔金,对高寒山区、工作空白区探索绿色、低成本、高效率的勘查评价技术方法势在必行,在此背景下逐渐形成适应阿尔金地区“天空地深”一体化找矿勘查评价体系[1]。该体系中“天”指遥感技术应用,即采用高清卫片结合谷歌地图等影像资料识别解译伟晶岩脉,圈定伟晶岩脉集中分布区域;“空”指无人机技术应用,即采用航空摄影及三维建模对地表伟晶岩延伸情况进行圈定;“地”指地面传统找矿手段应用,即采用路线地质调查、填图、槽探及采样分析等手段对无人机圈定的伟晶岩脉进行地面查证,圈定含矿伟晶岩脉;“深”指深部钻探手段应用,即采用便携式钻机了解含矿伟晶岩脉深部延伸及品位变化情况。该体系的应用可精准锁定找矿靶区,圈定矿(化)体,对矿区进行勘查评价,极大提高了找矿勘查效率,缩短找矿周期,在地形切割强烈的阿尔金地区值得广泛运用。

基于改进鲸鱼算法的多无人机协同欺骗干扰技术

多机协同对组网雷达系统进行航迹欺骗干扰属于大规模优化问题,往往需要利用群体智能算法优化无人机的飞行任务,然而采用传统群体智能算法优化时往往会出现收敛速度慢、求解精度低等问题。针对这一问题,对标准鲸鱼优化算法进行了改进,提出了一种基于改进鲸鱼优化算法的多无人机协同欺骗干扰技术。首先建立了多无人机协同欺骗干扰组网雷达的数学模型以及对应的优化函数,然后在标准鲸鱼优化算法的基础上引入了自适应惯性权值,提高了算法的全局搜索能力和收敛速度。仿真实验表明,固定无人机数量为9架时,利用改进鲸鱼、标准鲸鱼、粒子群、蚁群4种算法分别优化多机协同欺骗干扰模型,得出改进鲸鱼优化算法平均运行时间最短,迭代次数最少,同时优化产生的实际航迹与理论值误差最小;逐步增加无人机数量至20架,利用上述四种算法进行模型求解时得出改进鲸鱼优化算法在不同无人机架数的条件下产生的假目标航迹条数均优于其他3种算法。

我国低空经济的技术经济范式分析与发展对策

低空经济作为我国战略性新兴产业,具有典型的新质生产力特征。从低空经济的发展看,其符合技术经济范式的一般特征。低空经济发展遵循包含驱动力、新结构与新形态、价值创造活动、价值创造结果四要素的范式。目前,我国低空经济发展总体处于起步阶段,政策风口效应明显,发展前景广阔。依照技术经济范式,从驱动力看,我国正在逐步构建低空技术牵引、低空基础设施保障、低空经济政策助推的驱动力体系;从新结构与新形态看,我国低空经济已经广泛融入农业生产、观光旅游、物流配送、环境监测、应急救援等领域,在信息维度、能量维度、情绪维度的价值不断显现,同时部分城市依托低空经济产业链走出低空经济特色发展之路;从价值创造活动看,我国在低空飞行器制造、低空服务、低空运营维保等领域涌现出一批代表性企业,低空经济的场景和规模不断扩充,价值创造活动前景广阔;从价值创造结果看,近年来我国低空经济规模保持较快增长,在直接带动经济增长的同时展现出降低成本、提高效率、促进就业等社会效益。总体而言,发展低空经济是一项系统工程。尽管我国通用航空发展为低空经济奠定了基础,但与发达国家相比,我国低空经济发展仍然存在诸多不足,顶层设计亟待加强,体制机制有待理顺,技术创新有待加强,场景拓展有待加快,综合成本有待下降,行业保障有待提升。因此,应制定战略规划,统筹低空经济发展,优化低空空域管理,加大财政金融支持,推动低空经济产业链协同发展,加快技术创新与人才队伍建设,加强低空经济基础设施和法规标准体系建设以及安全保障。

巡检无人车激光SLAM与路径规划研究综述

激光同步定位与建图(SLAM)及路径规划是决定巡检无人车能否高效完成巡检任务的关键环节。围绕激光SLAM定位算法、环境地图、路径规划3个方面,从其优缺点、适用范围、改进方向出发,介绍了巡检无人车激光SLAM与路径规划研究的概况,系统阐述了国内外研究成果,分析了当前常见的技术难题,并对巡检无人车激光SLAM与路径规划的未来发展做出展望。

无人机在红豆杉国家种质资源收集区设计项目中的应用

无人机航测技术因其灵活高效的特点,被应用于林业三维地形图测制中,本文研究使用大疆精灵4RTK无人机对测区做竖直摄影,使用免像控技术,构建红豆杉国家种质资源收集区三维模型,为研究区域提供三维立体的视觉体验,为在种质收集区进行后续监测工作提供基础地理底座数据,通过分析三维模型精度满足林业基本图1∶10000的精度要求。

面向6G多维扩展的新型多址接入技术综述

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