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一种实现任意窄带光谱检测的有机光电探测器通用策略

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Science China Materials 2024年第3期67卷 852-862页

作者：朱玉秦灏郭婷婷杨艳青张哲张京李明朋陈红滨吴思敏韩蕊蔓万相见李光辉陈永胜 The Centre of Nanoscale Science and Technology and Key Laboratory of Functional Polymer Materials Institute of Polymer ChemistryTianjin Key Laboratory of Functional Polymer MaterialsCollege of Chemistryand Renewable Energy Conversion and Storage Center(RECAST)Nankai UniversityTianjin 300071China State Key Laboratory of Elemento-Organic Chemistry Nankai UniversityTianjin 300071China

窄带光电探测器因其优异的综合性能,在光谱仪、激光雷达、光通信和监控等关键应用领域广受欢迎.尽管窄带硅基探测器在当前市场上占据主导地位,但其本征刚性、光学带隙固定和尺寸大的特性极大地限制了其在新兴领域的应用,尤其是在柔性和... 详细信息

窄带光电探测器因其优异的综合性能,在光谱仪、激光雷达、光通信和监控等关键应用领域广受欢迎.尽管窄带硅基探测器在当前市场上占据主导地位,但其本征刚性、光学带隙固定和尺寸大的特性极大地限制了其在新兴领域的应用,尤其是在柔性和可穿戴光电子领域.在本工作中,我们报道了一种构筑窄带有机光电探测器(OPD)的简单通用策略.该策略通过溶液法将活性层中的给体和受体材料制备成光学调制层(OAL),并集成在OPD上,可实现对任意光谱的检测.利用该策略,我们成功地构筑了以750 nm为中心的窄带OPD,其半峰宽(FWHM)为40 nm,光谱响应率为3667,-3 dB截止频率为927 kHz,打破了自驱动窄带OPD的性能记录.值得注意的是,这种新颖的OAL策略在OPD中具有良好的通用性,可以实现对600至1000 nm范围内的任意窄光谱检测,具有FWHM可调(最小步长为2 nm)、响应度和探测率高、响应速度快的优势.受益于有机半导体固有的柔性特性,我们构筑了一种柔性且可弯曲的窄带近红外OPD线性阵列,并应用于全向激光雷达上,在无需机械旋转的情况下实现了360°水平扫描.

关键词： organic photodetector narrowband organic photodetector lidar flexible photodetector visible-near-infrared narrowband organic photodetector

Distribution and transport characteristics of fine particulate matter in beijing with mobile lidar measurements from 2015 to 2018

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Journal of Environmental Sciences 2022年第5期34卷 65-75页

作者： Lihui Lv Tianshu Zhang Yan Xiang Wenxuan Chai Wenqing Liu Information Materials and Intelligent Sensing Laboratory of Anhui Province Institutes of Physical Science and Information TechnologyAnhui UniversityHefei 230601China Key Laboratory of Environmental Optics and Technology Anhui Institute of Optics and Fine MechanicsChinese Academy of SciencesHefei 230031China China National Environmental Monitoring Centre Beijing 100012China

Accurately quantifying the concentration and transport flux of atmospheric fine particu-late matter(PM_(2.5))is vital when attempting to thoroughly identify the pollution formation mechanism.In this study,the mobile lidar measurements in Beijing on heavily polluted days in December from 2015 to 2018 are presented.The lidar was mounted on a vehicle,which could perform measurements along designated routes.On the basis of mobile lidar mea-surements along closed circuits of the 6th Ring Road around Beijing,the spatial distribution and transport flux of PM_(2.5) in Beijing were determined with information of wind field.In the spatial distribution,both the concentration and transport of PM_(2.5) were revealed to be more significant in the southern section of Beijing.The regional transport layer at heights<1.3 km plays an important role in pollution formation.The maximum transport flux reached 1600μg/(m^(2)*sec)on 11 December 2016.With the aerosol boundary layer height determined from the image edge detection(IED)method,the inter-annual variations of the aerosol boundary layer height(ABLH)were also analysed.The ABLH decreased from 0.73 to 0.46 km during the same heavy pollution period from 2015 to 2018.Increasingly adverse aerosol boundary layer(ABL)meteorological factors,including lower ABLH,light winds,temperature inversions,and accumulated moisture,have become necessary for pollution formation in Beijing.

关键词： Aerosol PM_(2.5) Regional transport lidar Mobile measurement

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填筑料碾压变形在线直接测量方法

水力发电学报 2024年第6期43卷 43-52页

作者：王祎翔段军邦张路吴高见刘天云清华大学水圈科学与水利工程全国重点实验室北京100084 清华大学水利部水圈科学重点实验室北京100084 清华大学水利水电工程系北京100084 青海黄河上游水电开发有限责任公司工程建设分公司西宁810003 中国水利水电第五工程局有限公司成都610066

在线直接检测填筑料的碾压变形是连续控制压实中亟待解决的问题。本文以填筑料碾压变形为研究对象,建立了基于平面激光束的碾压变形在线测量方法和系统。该方法采用激光测距和关键点定位确定碾压相对变形。基于现场试验,分析了碾压相对... 详细信息

在线直接检测填筑料的碾压变形是连续控制压实中亟待解决的问题。本文以填筑料碾压变形为研究对象,建立了基于平面激光束的碾压变形在线测量方法和系统。该方法采用激光测距和关键点定位确定碾压相对变形。基于现场试验,分析了碾压相对变形的演变过程。该系统实现了碾压相对变形在线直接检测,得到了填筑料碾压相对变形规律,有利于推动填筑工程智能建造技术的实际应用。

关键词：填筑工程在线检测 lidar 相对变形

Performance of lidar-SLAM-based PNT with initial poses based on NDT scan matching algorithm

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Satellite Navigation 2023年第1期4卷 113-127,I0004页

作者： Kaiwei Chiang Yuting Chiu Surachet Srinara Menglun Tsai Department of Geomatics Taiwan Cheng Kung UniversityNo.1Daxue Rd.East Dist.Tainan City 701TaiwanChina High Defnition Map Research Center Department of GeomaticsTaiwan Cheng Kung UniversityNo.1DaxueRd.East Dist.Tainan City 701TaiwanChina

To achieve higher automation level of vehicles defned by the Society of Automotive Engineers,safety is a key requirement afecting navigation accuracy.We apply Light Detection and Ranging(lidar)as a main auxiliary sensor and propose lidar-based Simultaneously Localization and Mapping(SLAM)approach for Positioning,Navigation,and Timing.Furthermore,point cloud registration is handled with 3D Normal Distribution Transform(NDT)method.The initial guess of the lidar pose for lidar-based SLAM comes from two sources:one is the diferential Global Navigation Satellite System(GNSS)solution;the other is Inertial Navigation System(INS)and GNSS integrated solution,generated with Extended Kalman Filter and motion constraints added,including Zero Velocity Update and Non-Holonomic Constraint.The experiment compares two initial guesses for scan matching in terms navigation accuracy.To emphasize the importance of a multi-sensor scheme in contrast to the conventional navigation method using the stand-alone system,the tests are conducted in both open sky area and GNSS signal block area,the latter might cause Multipath and Non-Line-Of-Sight efects.To enhance the navigation accuracy,the Fault Detection and Exclusion(FDE)mechanism is applied to correct the navigation outcome.The results show that the application of NDT and FDE for INS/GNSS integrated system can not only reach where-in-lane level navigation accuracy(0.5 m),but also enable constructing the dynamic map.

关键词： 3D NDT FDE INS/GNSS lidar PNT SLAM

Extraction and analysis of tree canopy height information in high-voltage transmission-line corridors by using integrated optical remote sensing and lidar

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Geodesy and Geodynamics 2023年第3期14卷 292-303页

作者： Jinpeng Hao Xiuguang Li Hong Wu Kai Yang Yumeng Zeng Yu Wang Yuanjin Pan State Grid Ningxia Electric Power Research Institute Yinchuan 750011China School of Electrical Engineering and Automation Wuhan UniversityWuhan 430061China School of Geodesy and Geomatics Wuhan UniversityWuhan 430079China Hubei LuoJia Laboratory Wuhan UniversityWuhan 430079China

Traditional inspection methods cannot quickly and accurately monitor tree barriers and safeguard the transmission lines.To solve these problems,in this study,we proposed a rapid canopy height information extraction method using optical remote sensing and lidar,and used UAV optical imagery with lidar to monitor the height of trees in a university and a high-voltage transmission line corridor in the Ningxia region.The results showed that the relative error of tree height extraction using UAV optical images was less than 5%,and the lowest relative error was 0.11%.The determination coefficient R^(2) between the optical image tree height extraction results and the measured tree height was 0.97,thus indicating a high correlation for both.In the field of tree barrier monitoring,the determination coefficient R^(2) of tree height extracted using airborne lidar point cloud,and canopy height model(CHM)and of the measured tree height were 0.947 and 0.931,respectively.The maximum and minimum relative error in tree height extraction performed using point cloud was 2.91%and 0.2%,respectively,with an extraction accuracy of over 95%.The experimental results demonstrated that it is feasible to use UAV optical remote sensing and lidar in monitoring tree barriers and tree height information extraction quickly and accurately,which is of great significance for the risk assessment and early warning of tree barriers in transmission-line corridors.

关键词： UAV lidar Power line Tree height

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面向侧视MLS点云的行道树单木分割方法

南京林业大学学报(自然科学版) 2024年

作者：严宇李秋洁李卫正南京林业大学机械电子工程学院

【目的】针对行道树资源调查中的行道树单木分割问题，研究面向侧视移动激光扫描（Mobile laser scanning，MLS）点云的行道树单木分割方法，对沿道路方向扫描采集到的街道两侧的点云，建立能够准确实现行道树单木分割的点云实例分割算... 详细信息

【目的】针对行道树资源调查中的行道树单木分割问题，研究面向侧视移动激光扫描（Mobile laser scanning，MLS）点云的行道树单木分割方法，对沿道路方向扫描采集到的街道两侧的点云，建立能够准确实现行道树单木分割的点云实例分割算法。【方法】对点云中的点提取局部特征，将局部特征输入到行道树点云检测器中在点云中识别出行道树点云；对于识别出的行道树点云采用基于密度的聚类算法（density-based spatial clustering of applications with noise，DBSCAN）进行聚类，在聚类簇中筛选出行道树簇并滤除非行道树点云；提取各行道树簇的树干点云，使用DBSCAN算法聚类得到若干个树干簇，统计每个行道树簇中包含的树干簇个数；对于包含多个树干簇的行道树簇使用垂直切片与垂直切割结合的方法将其粗分割为多颗单株行道树；使用DBSCAN与K近邻（k-Nearest Neighbor，KNN）相结合的方法对单株行道树进行细分割，得到最终的行道树单木分割结果。采集街道两侧的点云数据，开展了行道树点云检测器训练、细分割精度测试与算法对比3组实验。【结果】面向侧视MLS点云的行道树单木分割方法在点云数据上的精确率、召回率、F1分数分别为0.9704、0.9510、0.9606，优于已有的两种先识别再分割的方法。【结论】提出的方法可以准确实现对MLS点云中行道树的单木分割，为行道树资源调查工作节省人力成本。

关键词：行道树单木分割随机森林 DBSCAN聚类 lidar

Integrating Sentinel-1 and 2 with lidar data to estimate aboveground biomass of subtropical forests in northeast Guangdong, China

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International Journal of Digital Earth 2023年第1期16卷 158-182页

作者： Linjing Zhang Xiaoxue Zhang Zhenfeng Shao Wenhao Jiang Huimin Gao College of Geodesy and Geomatics Shandong University of Science and TechnologyQingdaoPeople’s Republic of China Key Laboratory of Ocean Geomatics Ministry of Natural ResourcesQingdaoPeople’s Republic of China State key Laboratory of Information Engineering in Surveying Mapping and Remote SensingWuhan UniversityWuhanPeople’s Republic of China

Accurate monitoring of forest aboveground biomass(AGB)is vital for sustainable forest management.Generally,the AGB is estimated by combining satellite images andfield measurements.Nevertheless,field plots are inaccessible in complex forest areas.Due to the limitations related to either optical or SAR data alone,combining the two data types is indispensable.Here,we explored the lidar-derived biomass as training/testing samples for the combination of yearly time-series of Sentinel-1 and Sentinel-2 images to estimate AGB in north-eastern Conghua,Guangdong province,China.The AGB reference map derived from airborne lidar data andfield plots could provide more samples for satellite-based AGB estimation with a limited amount of sampling plots.We designed four groups of experiments based on diverse Sentinel-1 and Sentinel-2 variables,including backscatter,backscatter indices,texture features,spectral bands,vegetation indices,and biophysical features.Four different prediction methods(support vector regression,multi-layer perceptron neural network,K-nearest neighbour,and random forest(RF))were separately used to estimate AGB.Results showed that the RF model achieved the best accuracy for AGB mapping.All Sentinel-1 and Sentinel-2 experiment(R^(2):0.72,RMSEr:17.65%)performed better than the monthly complementary experiment(R^(2):0.66,RMSEr:19.01%).Additionally,the arid period images were observed to be sensitive for estimating AGB.The most contributing Sentinels predictors were determined via a sequential forward selection.Consequently,the proposed methodology has great potential for low-cost,large-scale,and high-precision AGB estimation.

关键词： Sentinel lidar aboveground biomass non-parametric models subtropical forest

Radar style transfer for metric robot localisation on lidar maps

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CAAI Transactions on Intelligence Technology 2023年第1期8卷 139-148页

作者： Huan Yin Yue Wang Jun Wu Rong Xiong College of Control Science and Engineering Zhejiang UniversityHangzhouChina Department of Electronic and Computer Engineering Hong Kong University of Science and TechnologyKowloonHong KongChina

lidar and visual data are affected heavily in adverse weather conditions due to sensing mechanisms,which bring potential safety hazards for vehicle navigation.Radar sensing is desirable to build a more robust navigation system.In this paper,a cross-modality radar localisation on prior lidar maps is presented.Specifically,the proposed workflow consists of two parts:first,bird's-eye-view radar images are transferred to fake lidar images by training a generative adversarial network offline.Then with online radar scans,a Monte Carlo localisation framework is built to track the robot pose on lidar maps.The whole online localisation system only needs a rotating radar sensor and a pre-built global lidar map.In the experimental section,the authors conduct an ablation study on image settings and test the proposed system on Oxford Radar Robot Car Dataset.The promising results show that the proposed localisation system could track the robot pose successfully,thus demonstrating the feasibility of radar style transfer for metric robot localisation on lidar maps.

关键词： lidar local maps

A comparison of three surface roughness characterization techniques:photogrammetry,pin profiler,and smartphone-based lidar

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International Journal of Digital Earth 2022年第1期15卷 2422-2439页

作者： Zohreh Alijani Julien Meloche Alexander McLaren John Lindsay Alexandre Roy Aaron Berg Department of Geography Environment and GeomaticsUniversity of GuelphGuelphCanada Département de Géomatique Appliquée Université de SherbrookeSherbrookeCanada Département des Sciences de l’Environment Université du Québec à Trois-RivièresTrois-RivièresCanada

Surface roughness plays an important role in microwave remote sensing.In the agricultural domain,surface roughness is crucial for soil moisture retrieval methods that use electromagnetic surface scattering or microwave radiative transfer models.Therefore,improved characterization of Soil Surface Roughness(SSR)is of considerable importance.In this study,three approaches,including a standard pin profiler,a lidar point cloud generated from an iPhone 12 Pro,and a Structure from Motion(SfM)photogrammetric point cloud,were applied over 24 surface profiles with different roughness variations to measure surface roughness.The objective of this study was to evaluate the capability of smartphone-based lidar technology to measure surface roughness parameters and compare the results of this technique with the more common approaches.Results showed that the iPhone lidar technology,when point cloud data is captured in a fine-resolution mode,has a significant correlation with SfM photogrammetry(R2=0.70)and a relatively close agreement with pin profiler(R2=0.60).However,this accuracy tends to be greater for random surfaces and rough profiles with row structure orientations.The results of this study confirm that smartphone-based lidar can be used as a cost-effective,fast,and time-efficient alternative tool for measuring surface roughness,especially for rough,wide,and inaccessible areas.

关键词： lidar surface roughness structure from motion iPhone pin profiler