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1
Glukhov, V. A., and Yu A. Goldin. "Marine profiling lidars and their application for oceanological problems." Fundamental and Applied Hydrophysics 17, no. 1 (April 21, 2024): 104–28. http://dx.doi.org/10.59887/2073-6673.2024.17(1)-9.
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The review focuses on research conducted using profiling (radiometric) lidars. The paper presents the current state of lidar surveying equipment, methods for processing lidar data, and describes the problems of scientific and practical interest in oceanology that can be solved using lidar sensing. The review does not cover issues related to laser bathymetry, spectral (Raman) and spaceborne lidars, as they are separate specific fields. The main focus is on recent research in profiling lidar field. Summary tables of the technical characteristics of several of the most interesting airborne and shipborne lidars are provided. Their design features are discussed. Results from using lidars to determine near-surface hydrooptical characteristics, including employing polarization lidars and recently developed high-resolution spectral lidars, are presented. Findings from observing thin scattering layers across various aquatic regions are shown. The paper explores theoretical studies on lidar images of internal waves and experimental observations of internal waves in waters with different hydrooptical stratification. Lidars' application in addressing fisheries-related issues is examined. An overview of current development trends and future research directions is provided.
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Wang, Lihua, Michael J. Newchurch, Raul J. Alvarez II, Timothy A. Berkoff, Steven S. Brown, William Carrion, Russell J. De Young, et al. "Quantifying TOLNet ozone lidar accuracy during the 2014 DISCOVER-AQ and FRAPPÉ campaigns." Atmospheric Measurement Techniques 10, no. 10 (October 23, 2017): 3865–76. http://dx.doi.org/10.5194/amt-10-3865-2017.
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Abstract. The Tropospheric Ozone Lidar Network (TOLNet) is a unique network of lidar systems that measure high-resolution atmospheric profiles of ozone. The accurate characterization of these lidars is necessary to determine the uniformity of the network calibration. From July to August 2014, three lidars, the TROPospheric OZone (TROPOZ) lidar, the Tunable Optical Profiler for Aerosol and oZone (TOPAZ) lidar, and the Langley Mobile Ozone Lidar (LMOL), of TOLNet participated in the Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) mission and the Front Range Air Pollution and Photochemistry Éxperiment (FRAPPÉ) to measure ozone variations from the boundary layer to the top of the troposphere. This study presents the analysis of the intercomparison between the TROPOZ, TOPAZ, and LMOL lidars, along with comparisons between the lidars and other in situ ozone instruments including ozonesondes and a P-3B airborne chemiluminescence sensor. The TOLNet lidars measured vertical ozone structures with an accuracy generally better than ±15 % within the troposphere. Larger differences occur at some individual altitudes in both the near-field and far-field range of the lidar systems, largely as expected. In terms of column average, the TOLNet lidars measured ozone with an accuracy better than ±5 % for both the intercomparison between the lidars and between the lidars and other instruments. These results indicate that these three TOLNet lidars are suitable for use in air quality, satellite validation, and ozone modeling efforts.
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Newman, Jennifer F., and Andrew Clifton. "An error reduction algorithm to improve lidar turbulence estimates for wind energy." Wind Energy Science 2, no. 1 (February 10, 2017): 77–95. http://dx.doi.org/10.5194/wes-2-77-2017.
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Abstract. Remote-sensing devices such as lidars are currently being investigated as alternatives to cup anemometers on meteorological towers for the measurement of wind speed and direction. Although lidars can measure mean wind speeds at heights spanning an entire turbine rotor disk and can be easily moved from one location to another, they measure different values of turbulence than an instrument on a tower. Current methods for improving lidar turbulence estimates include the use of analytical turbulence models and expensive scanning lidars. While these methods provide accurate results in a research setting, they cannot be easily applied to smaller, vertically profiling lidars in locations where high-resolution sonic anemometer data are not available. Thus, there is clearly a need for a turbulence error reduction model that is simpler and more easily applicable to lidars that are used in the wind energy industry. In this work, a new turbulence error reduction algorithm for lidars is described. The Lidar Turbulence Error Reduction Algorithm, L-TERRA, can be applied using only data from a stand-alone vertically profiling lidar and requires minimal training with meteorological tower data. The basis of L-TERRA is a series of physics-based corrections that are applied to the lidar data to mitigate errors from instrument noise, volume averaging, and variance contamination. These corrections are applied in conjunction with a trained machine-learning model to improve turbulence estimates from a vertically profiling WINDCUBE v2 lidar. The lessons learned from creating the L-TERRA model for a WINDCUBE v2 lidar can also be applied to other lidar devices. L-TERRA was tested on data from two sites in the Southern Plains region of the United States. The physics-based corrections in L-TERRA brought regression line slopes much closer to 1 at both sites and significantly reduced the sensitivity of lidar turbulence errors to atmospheric stability. The accuracy of machine-learning methods in L-TERRA was highly dependent on the input variables and training dataset used, suggesting that machine learning may not be the best technique for reducing lidar turbulence intensity (TI) error. Future work will include the use of a lidar simulator to better understand how different factors affect lidar turbulence error and to determine how these errors can be reduced using information from a stand-alone lidar.
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Wing, Robin, Sophie Godin-Beekmann, Wolfgang Steinbrecht, Thomas J. McGee, John T. Sullivan, Sergey Khaykin, Grant Sumnicht, and Laurence Twigg. "Evaluation of the new DWD ozone and temperature lidar during the Hohenpeißenberg Ozone Profiling Study (HOPS) and comparison of results with previous NDACC campaigns." Atmospheric Measurement Techniques 14, no. 5 (May 25, 2021): 3773–94. http://dx.doi.org/10.5194/amt-14-3773-2021.
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Abstract. A newly upgraded German Weather Service (DWD) ozone and temperature lidar (HOH) located at the Hohenpeißenberg Meteorological Observatory (47.8∘ N, 11.0∘ E) has been evaluated through comparison with the travelling standard lidar operated by NASA's Goddard Space Flight Center (NASA GSFC Stratospheric Ozone (STROZ) lidar), satellite overpasses from the Microwave Limb Sounder (MLS), the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER), the Ozone Mapping and Profiler Suite (OMPS), meteorological radiosondes launched from Munich (65 km northeast), and locally launched ozonesondes. The “blind” evaluation was conducted under the framework of the Network for the Detection of Atmospheric Composition Change (NDACC) using 10 clear nights of measurements in 2018 and 2019. The campaign, referred to as the Hohenpeißenberg Ozone Profiling Study (HOPS), was conducted within the larger context of NDACC validation activities for European lidar stations. There was good agreement between all ozone lidar measurements in the range of 15 to 41 km with relative differences between co-located ozone profiles of less than ±10 %. Differences in the measured ozone number densities between the lidars and the locally launched ozone sondes were also generally less than 5 % below 30 km. The satellite ozone profiles demonstrated some differences with respect to the ground-based lidars which are due to sampling differences and geophysical variation. Both the original and new DWD lidars continue to meet the NDACC standard for lidar ozone profiles by exceeding 3 % accuracy between 16.5 and 43 km. Temperature differences for all instruments were less than ±5 K below 60 km, with larger differences present in the lidar–satellite comparisons above this region. Temperature differences between the DWD lidars met the NDACC accuracy requirements of ±1 K between 17 and 78 km. A unique cross-comparison between the HOPS campaign and a similar, recent campaign at Observatoire de Haute-Provence (Lidar Validation NDACC Experiment; LAVANDE) allowed for an investigation into potential biases in the NASA-STROZ reference lidar. The reference lidar may slightly underestimate ozone number densities above 43 km with respect to the French and German NDACC lidars. Below 20 km, the reference lidar temperatures profiles are 5 to 10 K cooler than the temperatures which are reported by the other instruments.
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Newchurch, Michael J., Raul J. Alvarez, Timothy A. Berkoff, William Carrion, Russell J. DeYoung, Rene Ganoe, Guillaume Gronoff, et al. "TOLNet ozone lidar intercomparison during the discover-aq and frappé campaigns." EPJ Web of Conferences 176 (2018): 10007. http://dx.doi.org/10.1051/epjconf/201817610007.
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The Tropospheric Ozone Lidar Network (TOLNet) is a unique network of lidar systems that measure atmospheric profiles of ozone and aerosols, to contribute to air-quality studies, atmospheric modeling, and satellite validation efforts. The accurate characterization of these lidars is of critical interest, and is necessary to determine cross-instrument calibration uniformity. From July to August 2014, three lidars, the TROPospheric OZone (TROPOZ) lidar, the Tunable Optical Profiler for Aerosol and oZone (TOPAZ) lidar, and the Langley Mobile Ozone Lidar (LMOL), of TOLNet participated in the “Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality” (DISCOVER-AQ) mission and the “Front Range Air Pollution and Photochemistry Éxperiment” (FRAPPÉ) to measure sub-hourly ozone variations from near the surface to the top of the troposphere. Although large differences occur at few individual altitudes in the near field and far field range, the TOLNet lidars agree with each other within ±4%. These results indicate excellent measurement accuracy for the TOLNet lidars that is suitable for use in air-quality and ozone modeling efforts.
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Chaikovsky, Anatoli, Oleg Dubovik, Brent Holben, Andrey Bril, Philippe Goloub, Didier Tanré, Gelsomina Pappalardo, et al. "Lidar-Radiometer Inversion Code (LIRIC) for the retrieval of vertical aerosol properties from combined lidar/radiometer data: development and distribution in EARLINET." Atmospheric Measurement Techniques 9, no. 3 (March 21, 2016): 1181–205. http://dx.doi.org/10.5194/amt-9-1181-2016.
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Abstract. This paper presents a detailed description of LIRIC (LIdar-Radiometer Inversion Code) algorithm for simultaneous processing of coincident lidar and radiometric (sun photometric) observations for the retrieval of the aerosol concentration vertical profiles. As the lidar/radiometric input data we use measurements from European Aerosol Research Lidar Network (EARLINET) lidars and collocated sun-photometers of Aerosol Robotic Network (AERONET). The LIRIC data processing provides sequential inversion of the combined lidar and radiometric data. The algorithm starts with the estimations of column-integrated aerosol parameters from radiometric measurements followed by the retrieval of height dependent concentrations of fine and coarse aerosols from lidar signals using integrated column characteristics of aerosol layer as a priori constraints. The use of polarized lidar observations allows us to discriminate between spherical and non-spherical particles of the coarse aerosol mode.The LIRIC software package was implemented and tested at a number of EARLINET stations. Intercomparison of the LIRIC-based aerosol retrievals was performed for the observations by seven EARLINET lidars in Leipzig, Germany on 25 May 2009. We found close agreement between the aerosol parameters derived from different lidars that supports high robustness of the LIRIC algorithm. The sensitivity of the retrieval results to the possible reduction of the available observation data is also discussed.
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Chaikovsky, A., O. Dubovik, B. Holben, A. Bril, P. Goloub, D. Tanré, G. Pappalardo, et al. "Lidar-Radiometer Inversion Code (LIRIC) for the retrieval of vertical aerosol properties from combined lidar/radiometer data: development and distribution in EARLINET." Atmospheric Measurement Techniques Discussions 8, no. 12 (December 7, 2015): 12759–822. http://dx.doi.org/10.5194/amtd-8-12759-2015.
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Abstract. This paper presents a detailed description of LIRIC (LIdar-Radiometer Inversion Code) algorithm for simultaneous processing of coincident lidar and radiometric (sun photometric) observations for the retrieval of the aerosol concentration vertical profiles. As the lidar/radiometric input data we use measurements from European Aerosol Research Lidar Network (EARLINET) lidars and collocated sun-photometers of Aerosol Robotic Network (AERONET). The LIRIC data processing provides sequential inversion of the combined lidar and radiometric data by the estimations of column-integrated aerosol parameters from radiometric measurements followed by the retrieval of height-dependent concentrations of fine and coarse aerosols from lidar signals using integrated column characteristics of aerosol layer as a priori constraints. The use of polarized lidar observations allows us to discriminate between spherical and non-spherical particles of the coarse aerosol mode. The LIRIC software package was implemented and tested at a number of EARLINET stations. Intercomparison of the LIRIC-based aerosol retrievals was performed for the observations by seven EARLNET lidars in Leipzig, Germany on 25 May 2009. We found close agreement between the aerosol parameters derived from different lidars that supports high robustness of the LIRIC algorithm. The sensitivity of the retrieval results to the possible reduction of the available observation data is also discussed.
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K, Mr Pramod, and Akshay M C. "LIDAR Technology." International Journal for Research in Applied Science and Engineering Technology 10, no. 5 (May 31, 2022): 2976–82. http://dx.doi.org/10.22214/ijraset.2022.43007.
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Abstract: Since the 1960s, LiDAR (Light Detection And Ranging) technology has been in use. LiDAR has become a common sensor as technology has advanced. Automation, agriculture, archaeology, Information technology and the quantification of various atmosphericcomponents all use LiDARs. The present manuscripts cover the operation of LiDAR, its various varieties, history, and various applications. One may determine the distance between different objects in space and construct a 3D digital representation of the region in front of LiDAR using LiDAR readings. Lidar mapping is a wellknown technique for quickly generating precise georeferenced spatial data about the Earth's shape and surface features. Lidar mapping systems and their underlying technology have recently progressed, allowing scientists and mapping professionals to investigate natural and built environments at sizes never before feasible, with greater accuracy, precision, and cost effectively provide the best aspects of the culture of human civilization. Keywords: LiDAR, LASER, RADAR
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Jie, Lu, Zhi Jin, Jinping Wang, Letian Zhang, and Xiaojun Tan. "A SLAM System with Direct Velocity Estimation for Mechanical and Solid-State LiDARs." Remote Sensing 14, no. 7 (April 4, 2022): 1741. http://dx.doi.org/10.3390/rs14071741.
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Simultaneous localization and mapping (SLAM) is essential for intelligent robots operating in unknown environments. However, existing algorithms are typically developed for specific types of solid-state LiDARs, leading to weak feature representation abilities for new sensors. Moreover, LiDAR-based SLAM methods are limited by distortions caused by LiDAR ego motion. To address the above issues, this paper presents a versatile and velocity-aware LiDAR-based odometry and mapping (VLOM) system. A spherical projection-based feature extraction module is utilized to process the raw point cloud generated by various LiDARs, hence avoiding the time-consuming adaptation of various irregular scan patterns. The extracted features are grouped into higher-level clusters to filter out smaller objects and reduce false matching during feature association. Furthermore, bundle adjustment is adopted to jointly estimate the poses and velocities for multiple scans, effectively improving the velocity estimation accuracy and compensating for point cloud distortions. Experiments on publicly available datasets demonstrate the superiority of VLOM over other state-of-the-art LiDAR-based SLAM systems in terms of accuracy and robustness. Additionally, the satisfactory performance of VLOM on RS-LiDAR-M1, a newly released solid-state LiDAR, shows its applicability to a wide range of LiDARs.
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Wang, Y., K. N. Sartelet, M. Bocquet, and P. Chazette. "Assimilation of ground versus lidar observations for PM<sub>10</sub> forecasting." Atmospheric Chemistry and Physics Discussions 12, no. 9 (September 7, 2012): 23291–331. http://dx.doi.org/10.5194/acpd-12-23291-2012.
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Abstract. This article investigates the potential impact of future ground-based lidar networks on analysis and short-term forecasts of particulate matter with a diameter smaller than 10 μg m−3 (PM10). To do so, an Observing System Simulation Experiment (OSSE) is built for PM10 data assimilation (DA) using optimal interpolation (OI) over Europe for one month in 2001. First, using a lidar network with 12 stations, we estimate the efficiency of assimilating the lidar network measurements in improving PM10 concentration analysis and forecast. It is compared to the efficiency of assimilating concentration measurements from the AirBase ground network, which includes about 500 stations in Western Europe. It is found that assimilating the lidar observations decreases by about 54% the root mean square error (RMSE) of PM10 concentrations after 12 h of assimilation and during the first forecast day, against 59% for the assimilation of AirBase measurements. However, the assimilation of lidar observations leads to similar scores as AirBase's during the second forecast day. The RMSE of the second forecast day is improved on average over the summer month by 57% by the lidar DA, against 56% by the AirBase DA. Moreover, the spatial and temporal influence of the assimilation of lidar observations is larger and longer. The results show a potentially powerful impact of the future lidar networks. Secondly, since a lidar is a costly instrument, a sensitivity study on the number and location of required lidars is performed to help defining an optimal lidar network for PM10 forecast. With 12 lidar stations, an efficient network in improving PM10 forecast over Europe is obtained by regularly spacing the lidars. DA with a lidar network of 26 or 76 stations is compared to DA with the previously-used lidar network. The assimilation of 76 lidar stations' measurements leads to a better score than AirBase's during the forecast days.
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Kelberlau, Felix, Vegar Neshaug, Lasse Lønseth, Tania Bracchi, and Jakob Mann. "Taking the Motion out of Floating Lidar: Turbulence Intensity Estimates with a Continuous-Wave Wind Lidar." Remote Sensing 12, no. 5 (March 10, 2020): 898. http://dx.doi.org/10.3390/rs12050898.
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Due to their motion, floating wind lidars overestimate turbulence intensity ( T I ) compared to fixed lidars. We show how the motion of a floating continuous-wave velocity–azimuth display (VAD) scanning lidar in all six degrees of freedom influences the T I estimates, and present a method to compensate for it. The approach presented here uses line-of-sight measurements of the lidar and high-frequency motion data. The compensation algorithm takes into account the changing radial velocity, scanning geometry, and measurement height of the lidar beam as the lidar moves and rotates. It also incorporates a strategy to synchronize lidar and motion data. We test this method with measurement data from a ZX300 mounted on a Fugro SEAWATCH Wind LiDAR Buoy deployed offshore and compare its T I estimates with and without motion compensation to measurements taken by a fixed land-based reference wind lidar of the same type located nearby. Results show that the T I values of the floating lidar without motion compensation are around 50 % higher than the reference values. The motion compensation algorithm detects the amount of motion-induced T I and removes it from the measurement data successfully. Motion compensation leads to good agreement between the T I estimates of floating and fixed lidar under all investigated wind conditions and sea states.
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Chen, Yiyin, Wei Yu, Feng Guo, and Po Wen Cheng. "Adaptive measuring trajectory for scanning lidars: proof of concept." Journal of Physics: Conference Series 2265, no. 2 (May 1, 2022): 022099. http://dx.doi.org/10.1088/1742-6596/2265/2/022099.
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Abstract Application of nacelle-mounted long-range scanning lidars is facing the challenge that the nacelle motion causes deviations in the measuring trajectories. Such lidars are very sensitive to even the slightest trajectory deviation due to its long measuring range. Motivated by this need, we propose the concept of adaptive measuring trajectory and explore its use for eliminating the effect of the rotational motion of the lidar on the target measuring trajectory. This work first aims to experimentally test the performance of adaptive measuring trajectory under ideal conditions by installing a scanning lidar on a 6DOF motion platform to model the lidar motion on the turbine nacelle. The real trajectory with and without correction is measured by a camera. The comparison confirms that the adaptive measuring trajectory could stablize the target measuring trajectory given the lidar motion. Then, the possibility of using Kalman filter to estimate lidar motion given noisy motion measurements is investigated. The results show great potential of Kalman filter for lidar motion estimation, which could be very useful for its future application.
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Yang, Shu, Fengchao Peng, Sibylle von Löwis, Guðrún Nína Petersen, and David Christian Finger. "Using Machine Learning Methods to Identify Particle Types from Doppler Lidar Measurements in Iceland." Remote Sensing 13, no. 13 (June 22, 2021): 2433. http://dx.doi.org/10.3390/rs13132433.
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Doppler lidars are used worldwide for wind monitoring and recently also for the detection of aerosols. Automatic algorithms that classify the lidar signals retrieved from lidar measurements are very useful for the users. In this study, we explore the value of machine learning to classify backscattered signals from Doppler lidars using data from Iceland. We combined supervised and unsupervised machine learning algorithms with conventional lidar data processing methods and trained two models to filter noise signals and classify Doppler lidar observations into different classes, including clouds, aerosols and rain. The results reveal a high accuracy for noise identification and aerosols and clouds classification. However, precipitation detection is underestimated. The method was tested on data sets from two instruments during different weather conditions, including three dust storms during the summer of 2019. Our results reveal that this method can provide an efficient, accurate and real-time classification of lidar measurements. Accordingly, we conclude that machine learning can open new opportunities for lidar data end-users, such as aviation safety operators, to monitor dust in the vicinity of airports.
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Hu, Mingxuan, Yajun Pang, and Long Gao. "Advances in Silicon-Based Integrated Lidar." Sensors 23, no. 13 (June 26, 2023): 5920. http://dx.doi.org/10.3390/s23135920.
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Silicon-based Lidar is an ideal way to reduce the volume of the Lidar and realize monolithic integration. It removes the moving parts in the conventional device and realizes solid-state beam steering. The advantages of low cost, small size, and high beam steering speed have attracted the attention of many researchers. In order to facilitate researchers to quickly understand the research progress and direction, this paper mainly describes the research progress of silicon-based integrated Lidar, including silicon-based optical phased array Lidar, silicon-based optical switch array Lidar, and continuous frequency-modulated wave Lidar. In addition, we also introduced the scanning modes and working principles of other kinds of Lidar, such as the Micro-Electro-Mechanical System, mechanical Lidar, etc., and analyzed the characteristics of the Lidars above. Finally, we summarized this paper and put forward the future expectations of silicon-based integrated Lidar.
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Yin, Zhenping, Longlong Wang, Yun He, and Xuan Wang. "Understanding the Roles of Aerosols and Clouds in Environment, Meteorology and Climate with Advanced Lidar Remote Sensing Techniques." Remote Sensing 16, no. 3 (February 4, 2024): 593. http://dx.doi.org/10.3390/rs16030593.
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This Special Issue lists nine publications, covering the topics of advanced atmospheric lidar techniques, lidar retrievals, and lidar applications. The investigations listed here are diverse, but they are all focused on atmospheric lidars. Some urgent issues, for instance low blind zone detection and polarization detection at a near-infrared wavelength band, were discussed and explored. The results are helpful for extending atmospheric lidar applications. In terms of lidar retrievals, a planetary boundary layer height retrieval and an automatic lidar retrieval for aerosol optical properties were investigated in some of the publications, which can strengthen the atmospheric lidar capabilities. For lidar applications, a detailed analysis of the evolution of stratospheric aerosol and dust–cloud interactions was presented. In this Editorial, the articles published within this Special Issue are reviewed to highlight their innovative contributions and main research findings.
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Amodeo, Aldo, Giuseppe D’Amico, Aldo Giunta, Nikolaos Papagiannopoulos, Alex Papayannis, Athina Argyrouli, Maria Mylonaki, et al. "ATHLI16: the ATHens Lidar Intercomparison campaign." EPJ Web of Conferences 176 (2018): 09008. http://dx.doi.org/10.1051/epjconf/201817609008.
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The results of the ATHLI16 (ATHens Lidar Intercomparison) campaign, held in Athens from 26/09 to 07/10 2016 are presented. The campaign was performed within the Lidar Calibration Centre activities (EU H2020 ACTRIS-2 project) to assess the performance of the EOLE lidar system (NTUA, Athens, Greece), operating within EARLINET, by comparing against the EARLINET reference lidar system MUSA (CNR-IMAA, Potenza, Italy). For both lidars only products retrieved by the EARLINET Single Calculus Chain have been compared.
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Wang, Y., K. N. Sartelet, M. Bocquet, and P. Chazette. "Assimilation of ground versus lidar observations for PM<sub>10</sub> forecasting." Atmospheric Chemistry and Physics 13, no. 1 (January 11, 2013): 269–83. http://dx.doi.org/10.5194/acp-13-269-2013.
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Abstract. This article investigates the potential impact of future ground-based lidar networks on analysis and short-term forecasts of particulate matter with a diameter smaller than 10 μm (PM10). To do so, an Observing System Simulation Experiment (OSSE) is built for PM10 data assimilation (DA) using optimal interpolation (OI) over Europe for one month from 15 July to 15 August 2001. First, using a lidar network with 12 stations and representing the "true" atmosphere by a simulation called "nature run", we estimate the efficiency of assimilating the lidar network measurements in improving PM10 concentration for analysis and forecast. It is compared to the efficiency of assimilating concentration measurements from the AirBase ground network, which includes about 500 stations in western Europe. It is found that assimilating the lidar observations decreases by about 54% the root mean square error (RMSE) of PM10 concentrations after 12 h of assimilation and during the first forecast day, against 59% for the assimilation of AirBase measurements. However, the assimilation of lidar observations leads to similar scores as AirBase's during the second forecast day. The RMSE of the second forecast day is improved on average over the summer month by 57% by the lidar DA, against 56% by the AirBase DA. Moreover, the spatial and temporal influence of the assimilation of lidar observations is larger and longer. The results show a potentially powerful impact of the future lidar networks. Secondly, since a lidar is a costly instrument, a sensitivity study on the number and location of required lidars is performed to help define an optimal lidar network for PM10 forecasts. With 12 lidar stations, an efficient network in improving PM10 forecast over Europe is obtained by regularly spacing the lidars. Data assimilation with a lidar network of 26 or 76 stations is compared to DA with the previously-used lidar network. During the first forecast day, the assimilation of 76 lidar stations' measurements leads to a better score (the RMSE decreased by about 65%) than AirBase's (the RMSE decreased by about 59%).
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Steinbrecht, W., T. J. McGee, L. W. Twigg, H. Claude, F. Schönenborn, G. K. Sumnicht, and D. Silbert. "Intercomparison of stratospheric ozone and temperature profiles during the October 2005 Hohenpeißenberg Ozone Profiling Experiment (HOPE)." Atmospheric Measurement Techniques 2, no. 1 (April 27, 2009): 125–45. http://dx.doi.org/10.5194/amt-2-125-2009.
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Abstract. Thirteen clear nights in October 2005 allowed successful intercomparison of the lidar operated since 1987 by the German Weather Service (DWD) at Hohenpeißenberg (47.8° N, 11.0° E) with the Network for the Detection of Atmospheric Composition Change (NDACC) travelling standard lidar operated by NASA's Goddard Space Flight Center. Both lidars provide ozone profiles in the stratosphere, and temperature profiles in the strato- and mesosphere. Additional ozone profiles came from on-site Brewer/Mast ozonesondes, additional temperature profiles from Vaisala RS92 radiosondes launched at Munich (65 km north-east), and from operational analyses by the US National Centers for Environmental Prediction (NCEP). The intercomparison confirmed a low bias for ozone from the DWD lidar in the 33 to 43 km region, by up to 10%. This bias is caused by the DWD ozone algorithm, and is consistent with previous comparisons of the DWD lidar with SAGE, GOMOS and other instruments. During HOPE, precision (repeatability) for ozone data from both lidars was better than 5% between 20 and 40 km altitude, dropping to 10% near 45 km, and to 50% near 50 km. These results are consistent with previous NDACC intercomparisons, and confirm the reliability of the NASA NDACC travelling standard lidar. Temperature from the DWD lidar showed a 1 to 2 K cold bias from 30 to 65 km against the NASA lidar, and a 2 to 4 K cold bias against radiosondes and NCEP. This is also consistent with previous intercomparisons. Temperature precision (repeatability) for the DWD lidar was better than 2 K from 30 to 50 km, decreasing to 10 K near 70 km. For the NASA lidar, precision is expected to be better than 1 K over the 30 to 70 km range. However, due to the much lower temperature precision of the DWD lidar, this could not be checked during HOPE. It was noted that the current DWD algorithm over-estimates temperature uncertainty, which should be reduced by a factor of 2.2 (e.g. from 22 K to 10 K near 70 km). The HOPE intercomparison did uncover a 290 m range error (upward shift) of the DWD lidar data. When this shift is removed, the bias of the ozone algorithm is corrected, and a better background estimation is used, ozone profiles from the DWD lidar agree very well with both the NASA lidar and SAGE. Systematic differences are then smaller than 3% between 20 and 44 km, and smaller than 5% between 17 and 47 km. These differences are close to zero, and are not (statistically) significant. The cold temperature bias against the NASA lidar also disappears when the DWD temperature processing is corrected for the 290 m range error, and more appropriate values for the Earth's gravity acceleration are used. Compared to the radiosondes or NCEP analyses, however, both lidars show 1 to 2 K lower temperatures over the entire 15 to 35 km range. Temperature and ozone variations are tracked well by both lidars, by ozone- and radiosondes, and by NCEP analyses. Correlations exceed 0.8 to 0.9 at most stratospheric levels. They decrease at levels above 40 km, especially for ozone or NCEP temperature. The ozone and temperature bias of the DWD lidar does not appear to have changed over time. Records of ozone and temperature from the DWD lidar should be consistent over the years. Nevertheless, the HOPE intercomparison was instrumental in uncovering and repairing several long-standing errors. HOPE also confirmed the reliability of the NASA lidar as a travelling standard. Now the entire DWD lidar data record needs to be reprocessed with the improved and revised algorithms.
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Hildebrand, J., G. Baumgarten, J. Fiedler, U. P. Hoppe, B. Kaifler, F. J. Lübken, and B. P. Williams. "Combined wind measurements by two different lidar instruments in the Arctic middle atmosphere." Atmospheric Measurement Techniques Discussions 5, no. 3 (June 12, 2012): 4123–56. http://dx.doi.org/10.5194/amtd-5-4123-2012.
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Abstract. During a joint campaign in January 2009 the Rayleigh/Mie/Raman (RMR) lidar and the sodium lidar at the ALOMAR Observatory (69° N, 16° E) in Northern Norway were operated simultaneously for more than 40 h, collecting data for wind measurements in the middle atmosphere from 30 up to 110 km altitude. At the upper (lower) altitude range where the RMR (sodium) lidar can operate, both lidars probe the same sounding volume, allowing to compare the derived wind speeds. We present the first simultaneous common volume wind measurements in the middle atmosphere using two different lidar instruments. The comparison of winds derived by RMR and sodium lidar is excellent for long integration times of 10 h as well as shorter ones of 1 h. Combination of data from both lidars allows identifying wavy structures between 30 and 110 km altitude, whose amplitudes increase with height. We have also performed lidar measurements of the same wind component using two independent branches of the RMR lidar and found a good agreement of the results but also identified inhomogeneities in the horizontal wind at about 55 km altitude of up to 20 ms−1. Such small scale inhomogeneities in the horizontal wind field are an essential challenge when comparing data from different instruments.
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Peña, Alfredo, Jakob Mann, and Nikolay Dimitrov. "Turbulence characterization from a forward-looking nacelle lidar." Wind Energy Science 2, no. 1 (March 13, 2017): 133–52. http://dx.doi.org/10.5194/wes-2-133-2017.
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Abstract. We present two methods to characterize turbulence in the turbine inflow using radial velocity measurements from nacelle-mounted lidars. The first uses a model of the three-dimensional spectral velocity tensor combined with a model of the spatial radial velocity averaging of the lidars, and the second uses the ensemble-averaged Doppler radial velocity spectrum. With the former, filtered turbulence estimates can be predicted, whereas the latter model-free method allows us to estimate unfiltered turbulence measures. Two types of forward-looking nacelle lidars are investigated: a pulsed system that uses a five-beam configuration and a continuous-wave system that scans conically. For both types of lidars, we show how the radial velocity spectra of the lidar beams are influenced by turbulence characteristics, and how to extract the velocity-tensor parameters that are useful to predict the loads on a turbine. We also show how the velocity-component variances and co-variances can be estimated from the radial-velocity unfiltered variances of the lidar beams. We demonstrate the methods using measurements from an experiment conducted at the Nørrekær Enge wind farm in northern Denmark, where both types of lidars were installed on the nacelle of a wind turbine. Comparison of the lidar-based along-wind unfiltered variances with those from a cup anemometer installed on a meteorological mast close to the turbine shows a bias of just 2 %. The ratios of the unfiltered and filtered radial velocity variances of the lidar beams to the cup-anemometer variances are well predicted by the spectral model. However, other lidar-derived estimates of velocity-component variances and co-variances do not agree with those from a sonic anemometer on the mast, which we mostly attribute to the small cone angle of the lidar. The velocity-tensor parameters derived from sonic-anemometer velocity spectra and those derived from lidar radial velocity spectra agree well under both near-neutral atmospheric stability and high wind-speed conditions, with differences increasing with decreasing wind speed and increasing stability. We also partly attribute these differences to the lidar beam configuration.
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Tong, Yicheng, Sijie Chen, Da Xiao, Kai Zhang, Jing Fang, Chong Liu, Yibing Shen, and Dong Liu. "Lidar Ratio Regional Transfer Method for Extinction Coefficient Accuracy Improvement in Lidar Networks." Remote Sensing 14, no. 3 (January 28, 2022): 626. http://dx.doi.org/10.3390/rs14030626.
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Lidar networks are essential to study the three-dimensional distribution of aerosols on a regional scale. At present, both Mie-scattering lidar (ML) and advanced lidars are being used in lidar networks. The latter can retrieve extinction coefficients without strict assumptions of the lidar ratio, such as Raman lidar (RL) or high-spectral-resolution lidar (HSRL). In order to balance the data quality and instrument costs for the lidar network, the lidar ratio regional transfer method in a lidar network is proposed in this paper. We developed a Lidar Ratio and Aerosol Fraction Non-linear Regression (LR-AFNR) model between the lidar ratio and corresponding absorbing aerosol fraction (this paper studied two types of absorbing aerosols: dust and carbonaceous). The aerosol fraction of the sun photometer retrieval was used as a medium to transfer the lidar ratio of HSRL retrieval to a certain range of MLs. This lidar ratio can be the input parameter for ML retrieval and enables the improvement of the extinction coefficient accuracy. The results show that the LR-APNR model is applicable to atmospheric conditions with high mineral dust or carbonaceous aerosol loading, and the maximum relative error of the ML extinction coefficient can be reduced from 46% (dust) and 64% (carbonaceous aerosol) to 20%.
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Vasileiadis, George, Patrick Brun, Omar Gabella, Stephane Rivoire, George Avdikos, Alexandros Louridas, George Georgoussis, and Alexandros Papayannis. "Design and Development of a Raman Lidar for Cherenkov Gamma Array Experiments." EPJ Web of Conferences 237 (2020): 07006. http://dx.doi.org/10.1051/epjconf/202023707006.
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Future Cherenkov Gamma Ray (CGR) experiments will reach a sensitivity and energy resolution never obtained until now by any other high energy gamma–ray experiment. It is well known that atmospheric conditions contribute particularly in this aspect. Raman lidars can help reduce the systematic uncertainties of the molecular and aerosol components of the atmosphere so these performances can be reached. The motivation for Raman lidars and the design and development of the Montpellier Raman lidar system is described. It provides both multiple elastic and Raman readout channels and custom-made optics design. Preliminary lidar tests and signals show the actual performance of the lidar in consistency with the desired goals.
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Wu, Jianqing, Hao Xu, and Wei Liu. "Points Registration for Roadside LiDAR Sensors." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 9 (May 9, 2019): 627–39. http://dx.doi.org/10.1177/0361198119843855.
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Roadside LiDAR deployment provides a solution to obtain the real-time high-resolution micro traffic data of unconnected road users for the connected-vehicle road network. Single roadside LiDAR sensor has a lot of limitations considering the scant coverage and the difficulty of handling object occlusion issue. Multiple roadside LiDAR sensors can provide a larger coverage and eliminate the object occlusion issue. To combine different LiDAR sensors, it is necessary to integrate the point clouds into the same coordinate system. The existing points registration methods serving mapping scans or autonomous sensing systems could not be directly used for roadside LiDAR sensors considering the different feature of point clouds and the spare points in the cost-effective roadside LiDAR sensors. This paper developed an approach for roadside LiDAR points registration. The developed points-aggregation-based partial iterative closest point algorithm (PA-PICP) is a semi-automatic points registration method, which contains two major parts: XY data registration and Z adjustment. A semi-automatic key point selection method was introduced. The partial iterative closest point was applied to minimize the difference between different LiDARs in the XY plane. The intersection of ground surface between different LiDARs was used for Z-axis adjustment. The performance of the developed procedure was evaluated with field-collected LiDAR data. The results showed the effectiveness and accuracy of data integration using PA-PICP was greatly improved compared with points registration using the traditional iterative closest point. The case studies also showed that the occlusion issue can be fixed after PA-PICP points registration.
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Steinmann Perez, Cedric D., Alan W. H. Lio, and Fanzhong Meng. "Analysis and evaluation of two reference LiDAR-assisted control designs for wind turbines." Journal of Physics: Conference Series 2767, no. 3 (June 1, 2024): 032048. http://dx.doi.org/10.1088/1742-6596/2767/3/032048.
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Abstract LiDAR-assisted wind turbine control holds promise in reducing structural loads and enhancing rotor speed regulation. However, a research gap exists in the practicality and limitations of commercially available fixed-beam LiDARs for large turbines and evaluating commonly employed LiDAR-assisted feedforward approaches. This study addresses these gaps by examining the implications of utilizing fixed-beam LiDARs in two wind turbine sizes and two reference LiDAR-assisted control strategies. A comprehensive evaluation considers coherence variations, uncertainties related to inaccurate pitch angle mapping with the upcoming wind speed, and their combined impact on load reduction. Numerical simulations reveal that an excessively low cut-off frequency in the low-pass filter can compromise preview time compensation. This is problematic in larger turbines, where coherence with limited LiDAR beams is inferior compared to smaller wind turbines, which deteriorates the effectiveness of the LiDAR-assisted control. Among the reference LiDAR-assisted control methods, the evaluation indicates the Schlipf approach has greater load reduction independence, while Bossanyi’s approach, which uses measurement of current blade pitch, yields positive results with fine-tuned baseline controllers. However, allowing baseline controller-induced frequencies to propagate into the controller may increase system excitation at certain frequencies due to the use of the actual pitch angle for feedforward pitch rate calculation.
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Steinbrecht, W., T. J. McGee, L. W. Twigg, H. Claude, F. Schönenborn, G. K. Sumnicht, and D. Silbert. "Intercomparison of stratospheric ozone and temperature profiles during the October 2005 Hohenpeissenberg Ozone Profiling Experiment (HOPE)." Atmospheric Measurement Techniques Discussions 2, no. 1 (January 12, 2009): 37–86. http://dx.doi.org/10.5194/amtd-2-37-2009.
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Abstract. Thirteen clear nights in October 2005 allowed successful intercomparison of the stationary lidar operated since 1987 by the German Weather Service (DWD) at Hohenpeissenberg (47.8° N, 11.0° E) with the Network for the Detection of Atmospheric Composition Change (NDACC) travelling standard lidar operated by NASA's Goddard Space Flight Center. Both lidars provide ozone profiles in the stratosphere, and temperature profiles in the strato- and mesosphere. Additional ozone profiles came from on-site Brewer/Mast ozonesondes, additional temperature profiles from Vaisala RS92 radiosondes launched at Munich (65 km north-east), and from operational analyses by the US National Centers for Environmental Prediction (NCEP). The intercomparison confirmed a low bias for ozone from the DWD lidar in the 33 to 43 km region, by up to 10%. This bias is caused by the DWD ozone algorithm. It will be removed in a future version. Between 20 and 33 km, agreement between both lidars, and ozonesondes below 30 km, is good with ozone differences less than 3 to 5%. Results are consistent with previous comparisons of the DWD lidar with SAGE, GOMOS and other satellite instruments. The intercomparison did uncover a 290 m upward shift of the DWD lidar data. When this shift is removed, agreement with ozone from the NASA lidar improves below 20 km, with remaining differences usually less than 5%, and not statistically significant. Precision (repeatability) for the lidar ozone data is better than 5% between 20 and 40 km altitude, dropping to 10% near 45 km, and 50% near 50 km. Temperature from the DWD lidar has a 1 to 2 K cold bias from 30 to 65 km against the NASA lidar, and a 2 to 4 K cold bias against radiosondes and NCEP. This is consistent with previous intercomparisons against NCEP or radiosondes. The cold bias against the NASA lidar disappears when the DWD lidar data are corrected for the afore-mentioned 290 m range error, and more appropriate values for the Earth's gravity acceleration are used. Temperature precision (repeatability) for the DWD lidar is better than 2 K between 30 and 50 km , decreasing to 10 K near 70 km. It is over-estimated by the current DWD algorithm, and should be reduced by a factor of 2.2 (e.g. from 22 K to 10 K near 70 km). Temperature and ozone variations are tracked well by both lidars, by ozone- and radiosondes, and by NCEP analyses. Correlations exceed 0.8 to 0.9 at most stratospheric levels. They decrease at levels above 40 km, especially for ozone or NCEP temperature. The ozone and temperature bias of the DWD lidar does not appear to have changed over the years. Long-term records of ozone and temperature from the DWD lidar should be consistent. Nevertheless, the HOPE intercomparison was instrumental in uncovering several long-standing errors. These need to be fixed and the entire DWD lidar data record needs to be reprocessed.
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Zhang, Mingshi, Yubing Wang, Qian Hu, Shuhua Zhao, Lei Liang, Yongyi Chen, Yuxin Lei, et al. "Phase-Modulated Continuous-Wave Coherent Ranging Method and Anti-Interference Evaluation." Applied Sciences 13, no. 9 (April 25, 2023): 5356. http://dx.doi.org/10.3390/app13095356.
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Light detection and ranging (LiDAR) has been applied in many areas because of its excellent performance. An easily achievable, cost-effective, and high-performance ranging method is a major challenge of LiDAR. Meanwhile, with the increasing applications of LiDAR, numerous LiDARs can be made to operate simultaneously, and potential interference is inevitable. Therefore, immunity against interference is paramount in LiDAR systems. In this paper, we demonstrated a ranging method referred to as phase-modulated continuous-wave (PhMCW). A detection range of 50 m and a ranging error of 2.2 cm are achieved. A one-dimensional scanning LiDAR system that is capable of detecting targets at 28 m is built, demonstrating the validation of the PhMCW method. Moreover, we propose a quantitative method for evaluating the anti-interference capability of lidar systems. The p-values of the Ljung–Box test were 0.0589 and 0.6327 for ToF and coherent LiDAR interferences, respectively, indicating that the PhMCW system is immune to interference. The proposed method can be applied to all types of LiDAR systems, regardless of the ranging method or beam-steering technique used.
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Wei, Weichen, Bijan Shirinzadeh, Rohan Nowell, Mohammadali Ghafarian, Mohamed M. A. Ammar, and Tianyao Shen. "Enhancing Solid State LiDAR Mapping with a 2D Spinning LiDAR in Urban Scenario SLAM on Ground Vehicles." Sensors 21, no. 5 (March 4, 2021): 1773. http://dx.doi.org/10.3390/s21051773.
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Solid-State LiDAR (SSL) takes an increasing share of the LiDAR market. Compared with traditional spinning LiDAR, SSLs are more compact, energy-efficient and cost-effective. Generally, the current study of SSL mapping is limited to adapting existing SLAM algorithms to an SSL sensor. However, compared with spinning LiDARs, SSLs are different in terms of their irregular scan patterns and limited FOV. Directly applying existing SLAM approaches on them often increase the instability of a mapping process. This study proposes a systematic design, which consists of a dual-LiDAR mapping system and a three DOF interpolated six DOF odometry. For dual-LiDAR mapping, this work uses a 2D LiDAR to enhance a 3D SSL performance on a ground vehicle platform. The proposed system takes a 2D LiDAR to preprocess the scanning field into a number of feature sections according to the curvatures on the 2D fraction. Subsequently, this section information is passed to 3D SSL for direction feature selection. Additionally, this work proposes an odometry interpolation method which uses both LiDARs to generate two separated odometries. The proposed odometry interpolation method selectively determines the appropriate odometry information to update the system state under challenging conditions. Experiments are conducted in different scenarios. The results proves that the proposed approach is able to utilise 12 times more corner features from the environment than the comparied method, thus results in a demonstrable improvement in its absolute position error.
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Mariani, Zen, Noah Stanton, James Whiteway, and Raisa Lehtinen. "Toronto Water Vapor Lidar Inter-Comparison Campaign." Remote Sensing 12, no. 19 (September 27, 2020): 3165. http://dx.doi.org/10.3390/rs12193165.
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This study presents comparisons between vertical water vapor profile measurements from a Raman lidar and a new pre-production broadband differential absorption lidar (DIAL). Vaisala’s novel DIAL system operates autonomously outdoors and measures the vertical profile of water vapor within the boundary layer 24 h a day during all weather conditions. Eight nights of measurements in June and July 2018 were used for the Toronto water vapor lidar inter-comparison field campaign. Both lidars provided reliable atmospheric backscatter and water vapor profile measurements. Comparisons were performed during night-time observations only, when the York Raman lidar could measure the water vapor profile. The purpose was to validate the water vapor profile measurements retrieved by the new DIAL system. The results indicate good agreement between the two lidars, with a mean difference (DIAL–Raman) of 0.17 ± 0.14 g/kg. There were two main causes for differences in their measurements: horizontal displacement between the two lidar sites (3.2 km) and vertical gradients in the water vapor profile. A case study analyzed during the campaign demonstrates the ability for both lidars to measure sudden changes and large gradients in the water vapor’s vertical structure due to a passing frontal system. These results provide an initial validation of the DIAL’s measurements and its ability to be implemented as part of an operational program.
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Wang, Yusheng, Yidong Lou, Yi Zhang, Weiwei Song, Fei Huang, and Zhiyong Tu. "A Robust Framework for Simultaneous Localization and Mapping with Multiple Non-Repetitive Scanning Lidars." Remote Sensing 13, no. 10 (May 20, 2021): 2015. http://dx.doi.org/10.3390/rs13102015.
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With the ability to provide long range, highly accurate 3D surrounding measurements, while lowering the device cost, non-repetitive scanning Livox lidars have attracted considerable interest in the last few years. They have seen a huge growth in use in the fields of robotics and autonomous vehicles. In virtue of their restricted FoV, they are prone to degeneration in feature-poor scenes and have difficulty detecting the loop. In this paper, we present a robust multi-lidar fusion framework for self-localization and mapping problems, allowing different numbers of Livox lidars and suitable for various platforms. First, an automatic calibration procedure is introduced for multiple lidars. Based on the assumption of rigidity of geometric structure, the transformation between two lidars can be configured through map alignment. Second, the raw data from different lidars are time-synchronized and sent to respective feature extraction processes. Instead of sending all the feature candidates for estimating lidar odometry, only the most informative features are selected to perform scan registration. The dynamic objects are removed in the meantime, and a novel place descriptor is integrated for enhanced loop detection. The results show that our proposed system achieved better results than single Livox lidar methods. In addition, our method outperformed novel mechanical lidar methods in challenging scenarios. Moreover, the performance in feature-less and large motion scenarios has also been verified, both with approvable accuracy.
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Liu, Zhengliang, Janet F. Barlow, Pak-Wai Chan, Jimmy Chi Hung Fung, Yuguo Li, Chao Ren, Hugo Wai Leung Mak, and Edward Ng. "A Review of Progress and Applications of Pulsed Doppler Wind LiDARs." Remote Sensing 11, no. 21 (October 28, 2019): 2522. http://dx.doi.org/10.3390/rs11212522.
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Doppler wind LiDAR (Light Detection And Ranging) makes use of the principle of optical Doppler shift between the reference and backscattered radiations to measure radial velocities at distances up to several kilometers above the ground. Such instruments promise some advantages, including its large scan volume, movability and provision of 3-dimensional wind measurements, as well as its relatively higher temporal and spatial resolution comparing with other measurement devices. In recent decades, Doppler LiDARs developed by scientific institutes and commercial companies have been well adopted in several real-life applications. Doppler LiDARs are installed in about a dozen airports to study aircraft-induced vortices and detect wind shears. In the wind energy industry, the Doppler LiDAR technique provides a promising alternative to in-situ techniques in wind energy assessment, turbine wake analysis and turbine control. Doppler LiDARs have also been applied in meteorological studies, such as observing boundary layers and tracking tropical cyclones. These applications demonstrate the capability of Doppler LiDARs for measuring backscatter coefficients and wind profiles. In addition, Doppler LiDAR measurements show considerable potential for validating and improving numerical models. It is expected that future development of the Doppler LiDAR technique and data processing algorithms will provide accurate measurements with high spatial and temporal resolutions under different environmental conditions.
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Wing, Robin, Wolfgang Steinbrecht, Sophie Godin-Beekmann, Thomas J. McGee, John T. Sullivan, Grant Sumnicht, Gérard Ancellet, Alain Hauchecorne, Sergey Khaykin, and Philippe Keckhut. "Intercomparison and evaluation of ground- and satellite-based stratospheric ozone and temperature profiles above Observatoire de Haute-Provence during the Lidar Validation NDACC Experiment (LAVANDE)." Atmospheric Measurement Techniques 13, no. 10 (October 22, 2020): 5621–42. http://dx.doi.org/10.5194/amt-13-5621-2020.
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Abstract. A two-part intercomparison campaign was conducted at Observatoire de Haute-Provence (OHP) for the validation of lidar ozone and temperature profiles using the mobile NASA Stratospheric Ozone Lidar (NASA STROZ), satellite overpasses from the Microwave Limb Sounder (MLS), the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER), meteorological radiosondes launched from Nîmes, and locally launched ozonesondes. All the data were submitted and compared “blind”, before the group could see results from the other instruments. There was good agreement between all ozone measurements between 20 and 40 km, with differences of generally less than 5 % throughout this region. Below 20 km, SABER and MLS measured significantly more ozone than the lidars or ozonesondes. Temperatures for all lidars were in good agreement between 30 and 60 km, with differences on the order of ±1 to 3 K. Below 30 km, the OHP lidar operating at 532 nm has a significant cool bias due to contamination by aerosols. Systematic, altitude-varying bias up to ±5 K compared to the lidars was found for MLS at many altitudes. SABER temperature profiles are generally closer to the lidar profiles, with up 3 K negative bias near 50 km. Total uncertainty estimates for ozone and temperature appear to be realistic for nearly all systems. However, it does seem that the very low estimated uncertainties of lidars between 30 and 50 km, between 0.1 and 1 K, are not achieved during Lidar Validation Network for the Detection of Atmospheric Composition Change (NDACC) Experiment (LAVANDE). These estimates might have to be increased to 1 to 2 K.
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Nevzorov, Alexey A., Alexey V. Nevzorov, Olga Kharchenko, and Yaroslav O. Romanovskii. "Lidar Complex for Control of the Ozonosphere over Tomsk, Russia." Atmosphere 15, no. 6 (May 22, 2024): 622. http://dx.doi.org/10.3390/atmos15060622.
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We present a union of three measurement systems on the basis of the Siberian lidar station and mobile ozone lidar. The lidars are designed for studying the ozonosphere using the method of differential absorption and scattering, as well as for studying aerosol fields using elastic single scattering. The systems are constructed on the basis of Nd:YAG lasers (SOLAR) and an Nd:YAG laser (LOTIS TII), a XeCl laser (Lambda Physik) and receiving telescopes assembled using the Kassegrain system with a diameter 0.35 m and the Newtonian 0.5 m system. Lidars operate in photon-counting mode and record lidar signals with a spatial resolution from 1.5 m to 160 m at sensing wavelengths of 299/341 nm in the altitude range of ~0.1–12 km and ~5–20, and at 308/353 nm in the altitude range of ~15–45 km. The union of these three measurement systems was used to carry out field experiments of atmospheric lidar sensing in Tomsk and to present the results of retrieving the vertical profile of the ozone concentration. In this study, coverage of the entire ozonosphere by the lidars was carried out for the first time in Russia.
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Sox, Leda, Vincent B. Wickwar, Tao Yuan, and Neal R. Criddle. "Comparison of rayleigh-scatter and sodium resonance lidar temperatures." EPJ Web of Conferences 176 (2018): 03005. http://dx.doi.org/10.1051/epjconf/201817603005.
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We present an unprecedented comparison of temperature measurements from the Rayleigh-scatter (RS) and sodium (Na) lidar techniques. The extension of the RS technique into the lower thermosphere that has been achieved by the group at Utah State University (USU), enables simultaneous, common-volume measurements by the two lidar systems hosted in the Atmospheric Lidar Observatory at USU. The two lidars’ nightly averaged temperatures from 80-105 km, based on 19 nights of observations, are explored.
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Fu, Wei, Alessandro Sebastiani, Alfredo Peña, and Jakob Mann. "Dependence of turbulence estimations on nacelle lidar scanning strategies." Wind Energy Science 8, no. 5 (May 4, 2023): 677–90. http://dx.doi.org/10.5194/wes-8-677-2023.
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Abstract. Through numerical simulations and the analysis of field measurements, we investigate the dependence of the accuracy and uncertainty of turbulence estimations on the main features of the nacelle lidars' scanning strategy, i.e., the number of measurement points, the half-cone opening angle, the focus distance and the type of the lidar system. We assume homogeneous turbulence over the lidar scanning area in front of a Vestas V52 wind turbine. The Reynolds stresses are computed via a least-squares procedure that uses the radial velocity variances of each lidar beam without the need to reconstruct the wind components. The lidar-retrieved Reynolds stresses are compared with those from a sonic anemometer at turbine hub height. Our findings from the analysis of both simulations and measurements demonstrate that to estimate the six Reynolds stresses accurately, a nacelle lidar system with at least six beams is required. Further, one of the beams of this system should have a different opening angle. Adding one central beam improves the estimations of the velocity components' variances. Assuming the relations of the velocity components' variances as suggested in the IEC standard, all considered lidars can estimate the along-wind variance accurately using the least-squares procedure and the Doppler radial velocity spectra. Increasing the opening angle increases the accuracy and reduces the uncertainty on the transverse components, while enlarging the measurement distance has opposite effects. All in all, a six-beam continuous-wave lidar measuring at a close distance with a large opening angle provides the best estimations of all Reynolds stresses. This work gives insights on designing and utilizing nacelle lidars for inflow turbulence characterization.
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Hildebrand, J., G. Baumgarten, J. Fiedler, U. P. Hoppe, B. Kaifler, F. J. Lübken, and B. P. Williams. "Combined wind measurements by two different lidar instruments in the Arctic middle atmosphere." Atmospheric Measurement Techniques 5, no. 10 (October 19, 2012): 2433–45. http://dx.doi.org/10.5194/amt-5-2433-2012.
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Abstract. During a joint campaign in January 2009, the Rayleigh/Mie/Raman (RMR) lidar and the sodium lidar at the ALOMAR Observatory (69° N, 16° E) in Northern Norway were operated simultaneously for more than 40 h, collecting data for wind measurements in the middle atmosphere from 30 up to 110 km altitude. As both lidars share the same receiving telescopes, the upper altitude range of the RMR lidar and the lower altitude range of the sodium lidar overlap in the altitude region of ≈80–85 km. For this overlap region we are thus able to present the first simultaneous wind measurements derived from two different lidar instruments. The comparison of winds derived by RMR and sodium lidar is excellent for long integration times of 10 h as well as shorter ones of 1 h. Combination of data from both lidars allows identifying wavy structures between 30 and 110 km altitude, whose amplitudes increase with height. We have also performed vertical wind measurements and measurements of the same horizontal wind component using two independent lasers and telescopes of the RMR lidar and show how to use this data to calibrate and validate the wind retrieval. For the latter configuration we found a good agreement of the results but also identified inhomogeneities in the horizontal wind at about 55 km altitude of up to 20 ms−1 for an integration time of nearly 4 h. Such small-scale inhomogeneities in the horizontal wind field are an essential challenge when comparing data from different instruments.
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Gong, Shunjie, Chenghao Shi, Hui Zhang, Huimin Lu, Zhiwen Zeng, and Xieyuanli Chen. "RSS-LIWOM: Rotating Solid-State LiDAR for Robust LiDAR-Inertial-Wheel Odometry and Mapping." Remote Sensing 15, no. 16 (August 15, 2023): 4040. http://dx.doi.org/10.3390/rs15164040.
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Solid-state LiDAR offers multiple advantages over mechanism mechanical LiDAR, including higher durability, improved coverage ratio, and lower prices. However, solid-state LiDARs typically possess a narrow field of view, making them less suitable for odometry and mapping systems, especially for mobile autonomous systems. To address this issue, we propose a novel rotating solid-state LiDAR system that incorporates a servo motor to continuously rotate the solid-state LiDAR, expanding the horizontal field of view to 360°. Additionally, we propose a multi-sensor fusion odometry and mapping algorithm for our developed sensory system that integrates an IMU, wheel encoder, motor encoder and the LiDAR into an iterated Kalman filter to obtain a robust odometry estimation. Through comprehensive experiments, we demonstrate the effectiveness of our proposed approach in both outdoor open environments and narrow indoor environments.
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Cholleton, Danaël, Patrick Rairoux, and Alain Miffre. "Laboratory Evaluation of the (355, 532) nm Particle Depolarization Ratio of Pure Pollen at 180.0° Lidar Backscattering Angle." Remote Sensing 14, no. 15 (August 5, 2022): 3767. http://dx.doi.org/10.3390/rs14153767.
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While pollen is expected to impact public human health and the Earth’s climate more and more in the coming decades, lidar remote sensing of pollen has become an important developing research field. To differentiate among the pollen taxa, a polarization lidar is an interesting tool since pollen exhibit non-spherical complex shapes. A key attribute is thus the lidar particle depolarization ratio (PDR) of pollen, which is however difficult to quantify as pollen are large and complex-shaped particles, far beyond the reach of light scattering numerical simulations. In this paper, a laboratory π-polarimeter is used to accurately evaluate the PDR of pure pollen, for the first time at the lidar exact backscattering angle of 180.0°. We hence reveal the lidar PDR of pure ragweed, ash, birch, pine, cypress and spruce pollens at 355 and 532 nm lidar wavelengths, as presented at the ELC 2021 conference. A striking result is the spectral dependence of the lidar PDR, highlighting the importance of dual-wavelength (or more) polarization lidars to identify pollen taxa. These spectral and polarimetric fingerprints of pure pollen, as they are accurate, can be used by the lidar community to invert multi-wavelength lidar polarization measurements involving pollen.
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Stawiarski, Christina, Katja Träumner, Christoph Knigge, and Ronald Calhoun. "Scopes and Challenges of Dual-Doppler Lidar Wind Measurements—An Error Analysis." Journal of Atmospheric and Oceanic Technology 30, no. 9 (September 1, 2013): 2044–62. http://dx.doi.org/10.1175/jtech-d-12-00244.1.
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Abstract Pulsed Doppler lidars are powerful tools for long-range, high-resolution measurements of radial wind velocities. With the development of commercial Doppler lidars and the reduction of acquisition costs, dual-Doppler lidar systems will be become increasingly accessible in upcoming years. This study reviews the most common dual-Doppler techniques, describes the setup of a highly synchronized long-range dual-Doppler lidar system, and discusses extensively the different kinds of errors connected with this complex measurement technique. Sources of errors and their interactions are traced through the retrieval algorithm, including errors from single-Doppler lidar and those occurring from a combination of instruments related to various parameters, such as relative beam angles, time and spatial scales of the scan pattern, and atmospheric conditions.
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Newman, Jennifer F., Petra M. Klein, Sonia Wharton, Ameya Sathe, Timothy A. Bonin, Phillip B. Chilson, and Andreas Muschinski. "Evaluation of three lidar scanning strategies for turbulence measurements." Atmospheric Measurement Techniques 9, no. 5 (May 3, 2016): 1993–2013. http://dx.doi.org/10.5194/amt-9-1993-2016.
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Abstract. Several errors occur when a traditional Doppler beam swinging (DBS) or velocity–azimuth display (VAD) strategy is used to measure turbulence with a lidar. To mitigate some of these errors, a scanning strategy was recently developed which employs six beam positions to independently estimate the u, v, and w velocity variances and covariances. In order to assess the ability of these different scanning techniques to measure turbulence, a Halo scanning lidar, WindCube v2 pulsed lidar, and ZephIR continuous wave lidar were deployed at field sites in Oklahoma and Colorado with collocated sonic anemometers.Results indicate that the six-beam strategy mitigates some of the errors caused by VAD and DBS scans, but the strategy is strongly affected by errors in the variance measured at the different beam positions. The ZephIR and WindCube lidars overestimated horizontal variance values by over 60 % under unstable conditions as a result of variance contamination, where additional variance components contaminate the true value of the variance. A correction method was developed for the WindCube lidar that uses variance calculated from the vertical beam position to reduce variance contamination in the u and v variance components. The correction method reduced WindCube variance estimates by over 20 % at both the Oklahoma and Colorado sites under unstable conditions, when variance contamination is largest. This correction method can be easily applied to other lidars that contain a vertical beam position and is a promising method for accurately estimating turbulence with commercially available lidars.
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Newman, J. F., P. M. Klein, S. Wharton, A. Sathe, T. A. Bonin, P. B. Chilson, and A. Muschinski. "Evaluation of three lidar scanning strategies for turbulence measurements." Atmospheric Measurement Techniques Discussions 8, no. 11 (November 24, 2015): 12329–81. http://dx.doi.org/10.5194/amtd-8-12329-2015.
Full textAbstract:
Abstract. Several errors occur when a traditional Doppler-beam swinging (DBS) or velocity–azimuth display (VAD) strategy is used to measure turbulence with a lidar. To mitigate some of these errors, a scanning strategy was recently developed which employs six beam positions to independently estimate the u, v, and w velocity variances and covariances. In order to assess the ability of these different scanning techniques to measure turbulence, a Halo scanning lidar, WindCube v2 pulsed lidar and ZephIR continuous wave lidar were deployed at field sites in Oklahoma and Colorado with collocated sonic anemometers. Results indicate that the six-beam strategy mitigates some of the errors caused by VAD and DBS scans, but the strategy is strongly affected by errors in the variance measured at the different beam positions. The ZephIR and WindCube lidars overestimated horizontal variance values by over 60 % under unstable conditions as a result of variance contamination, where additional variance components contaminate the true value of the variance. A correction method was developed for the WindCube lidar that uses variance calculated from the vertical beam position to reduce variance contamination in the u and v variance components. The correction method reduced WindCube variance estimates by over 20 % at both the Oklahoma and Colorado sites under unstable conditions, when variance contamination is largest. This correction method can be easily applied to other lidars that contain a vertical beam position and is a promising method for accurately estimating turbulence with commercially available lidars.
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Duong, Huu Toan, and Young Soo Suh. "A Human Gait Tracking System Using Dual Foot-Mounted IMU and Multiple 2D LiDARs." Sensors 22, no. 17 (August 24, 2022): 6368. http://dx.doi.org/10.3390/s22176368.
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This paper proposes a human gait tracking system using a dual foot-mounted IMU and multiple 2D LiDARs. The combining system aims to overcome the disadvantages of each single sensor system (the short tracking range of the single 2D LiDAR and the drift errors of the IMU system). The LiDARs act as anchors to mitigate the errors of an inertial navigation algorithm. In our system, two 2D LiDARs are used. LiDAR 1 is placed around the starting point, and LiDAR 2 is placed at the ending point (in straight walking) or at the turning point (in rectangular path walking). Using the LiDAR 1, we can estimate the initial headings and positions of each IMU without any calibration process. We also propose a method to calibrate two LiDARs that are placed far apart. Then, the measurement from two LiDARs can be combined in a Kalman filter and the smoother algorithm to correct the two estimated feet trajectories. If straight walking is detected, we update the current stride heading and the foot position using the previous stride headings. Then, it is used as a measurement update in the Kalman filter. In the smoother algorithm, a step width constraint is used as a measurement update. We evaluate the stride length estimation through a straight walking experiment along a corridor. The root mean square errors compared with an optical tracking system are less than 3 cm. The performance of proposed method is also verified with a rectangular path walking experiment.
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Alsadik, Bashar. "Ideal Angular Orientation of Selected 64-Channel Multi Beam Lidars for Mobile Mapping Systems." Remote Sensing 12, no. 3 (February 5, 2020): 510. http://dx.doi.org/10.3390/rs12030510.
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Lidar technology is thriving nowadays for different applications mainly for autonomous navigation, mapping, and smart city technology. Lidars vary in different aspects and can be: multi beam, single beam, spinning, solid state, full 360 field of view FOV, single or multi pulse returns, and many other geometric and radiometric aspects. Users and developers in the mapping industry are continuously looking for new released Lidars having high properties of output density, coverage, and accuracy while keeping a lower cost. Accordingly, every Lidar type should be well evaluated for the final intended mapping aim. This evaluation is not easy to implement in practice because of the need to have all the investigated Lidars available in hand and integrated into a ready to use mapping system. Furthermore, to have a fair comparison; it is necessary to ensure the test applied in the same environment at the same travelling path among other conditions. In this paper, we are evaluating two state-of-the-art multi beam Lidar types: Ouster OS-1-64 and Hesai Pandar64 for mapping applications. The evaluation of the Lidar types is applied in a simulation environment which approximates reality. The paper shows the determination of the ideal orientation angle for the two Lidars by assessing the density, coverage, and accuracy and presenting clear performance quantifications and conclusions.
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Polenin, V. "Application of lidars in the monitoring system of hydrophysical disturbances from moving objects." Transactions of the Krylov State Research Centre 3, no. 397 (August 6, 2021): 127–32. http://dx.doi.org/10.24937/2542-2324-2021-3-397-127-132.
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Object and purpose of research. The object of this research study is a physical phenomenon of lidar observation of hydrophysical disturbances from an object moving underwater confirmed by the scientific discovery registered with Russian Academy of Natural Sciences (RANS). The purpose is to briefly present the phenomenon essence and to validate the feasibility of underwater monitoring system involving lidars. Materials and methods. The work materials is the phenomenon description and publications confirming its reliability. The feasibility of underwater monitoring system employing lidars is validated by model representation of this system as a group of distributed fixed lidars, which record time instants when a moving underwater object is passing by. The navigation task of locating its coordinates and parameters of motion is solved. Main results. The results demonstrate exact solutions to the problem implemented in MATLAB programming system, which confirms that the model is adequate and its software implementation is correct. Conclusion. The purpose of the work to examine the feasibility of lidar underwater monitoring system is achieved. The new scientific results are the problem formulation and the method of solving a navigation problem to find coordinates and parameters of motion from lidar-detected instants of hydrophysical disturbances. A hypothetical lidar-based monitoring system, if verified experimentally that lidars are sufficiently long-range instruments, is a promising idea.
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Alexeev, Valeriy, Dmitry Goryachkin, Nikolay Gryaznov, Viktor Kuprenyuk, and Evgeniy Sosnov. "Prospects for using gated lidars in autonomous mobile robots." Robotics and Technical Cybernetics 9, no. 2 (June 30, 2021): 133–41. http://dx.doi.org/10.31776/rtcj.9208.
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The analysis of the implementation problems of technical vision systems based on the use of time-of-flight laser lidars is carried out. It is concluded that the implementation of vision systems with acceptable parameters dictates an excessively high cost of the lidar. An alternative version of the lidar implementation is considered – a gated lidar based on a laser vision system. Replacing the broadband detector and high-speed scanning system with a gated CCD-matrix can significantly reduce the cost of the lidar while ensuring the high resolution of the lidar. The analysis of the dependence of the signal-to-noise ratio for gated lidar with and without an electron-optical converter has shown that in bad weather conditions the decrease in the gain of the useful signal when the image intensifier is excluded is compensated by the exclusion of the EOC's noise factor, so that the loss in the observation distance is less than 15%.
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Wing, Robin, Alain Hauchecorne, Philippe Keckhut, Sophie Godin-Beekmann, Sergey Khaykin, Emily M. McCullough, Jean-François Mariscal, and Éric d'Almeida. "Lidar temperature series in the middle atmosphere as a reference data set – Part 1: Improved retrievals and a 20-year cross-validation of two co-located French lidars." Atmospheric Measurement Techniques 11, no. 10 (October 10, 2018): 5531–47. http://dx.doi.org/10.5194/amt-11-5531-2018.
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Abstract. The objective of this paper and its companion (Wing et al., 2018) is to show that ground-based lidar temperatures are a stable, accurate, and precise data set for use in validating satellite temperatures at high vertical resolution. Long-term lidar observations of the middle atmosphere have been conducted at the Observatoire de Haute-Provence (OHP), located in southern France (43.93∘ N, 5.71∘ E), since 1978. Making use of 20 years of high-quality co-located lidar measurements, we have shown that lidar temperatures calculated using the Rayleigh technique at 532 nm are statistically identical to lidar temperatures calculated from the non-absorbing 355 nm channel of a differential absorption lidar (DIAL) system. This result is of interest to members of the Network for the Detection of Atmospheric Composition Change (NDACC) ozone lidar community seeking to produce validated temperature products. Additionally, we have addressed previously published concerns of lidar–satellite relative warm bias in comparisons of upper-mesospheric and lower-thermospheric (UMLT) temperature profiles. We detail a data treatment algorithm which minimizes known errors due to data selection procedures, a priori choices, and initialization parameters inherent in the lidar retrieval. Our algorithm results in a median cooling of the lidar-calculated absolute temperature profile by 20 K at 90 km altitude with respect to the standard OHP NDACC lidar temperature algorithm. The confidence engendered by the long-term cross-validation of two independent lidars and the improved lidar temperature data set is exploited in Wing et al. (2018) for use in multi-year satellite validations.
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Fu, Wei, Feng Guo, David Schlipf, and Alfredo Peña. "Feedforward pitch control for a 15 MW wind turbine using a spinner-mounted single-beam lidar." Wind Energy Science 8, no. 12 (December 19, 2023): 1893–907. http://dx.doi.org/10.5194/wes-8-1893-2023.
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Abstract. Feedforward blade pitch control is one of the most promising lidar-assisted control strategies due to its significant improvement in rotor speed regulation and fatigue load reduction. A high-quality preview of the rotor-effective wind speed is a key element of control benefits. In this work, a single-beam lidar is simulated in the spinner of a bottom-fixed IEA 15 MW wind turbine. Both continuous-wave (CW) and pulsed lidar systems are considered. The single-beam lidar can rotate with the wind turbine rotor and scan the inflow with a circular pattern, which mimics a multiple-beam nacelle lidar at a lower cost. Also, the spinner-based lidar has an unimpeded view of the inflow without intermittent blockage from the rotating blade. The focus distance and the cone angle of the spinner-based single-beam lidar are optimized for the best wind preview quality based on a rotor-effective wind speed coherence model. Then, the control benefits of using the optimized spinner-based lidar are evaluated for an above-rated wind speed in OpenFAST with an embedded lidar simulator and virtual four-dimensional Mann turbulence fields considering the wind evolution. Results are compared against those using a single-beam nacelle-based lidar. We found that the optimum scanning configurations of both CW and pulsed spinner-based single-beam lidars lead to a lidar scan radius of 0.6 of the rotor radius. Also, results show that a single-beam lidar mounted in the spinner provides many more control benefits (i.e. better rotor speed regulations and higher reductions in the damage equivalent loads on the tower base and blade roots) than the one based on the nacelle. The spinner-based single-beam lidar has a similar performance to a four-beam nacelle lidar when used for feedforward control.
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Hansen, Johannes N., Steven Hancock, Ludwig Prade, Gerald M. Bonner, Haochang Chen, Ian Davenport, Brynmor E. Jones, and Matthew Purslow. "Assessing Novel Lidar Modalities for Maximizing Coverage of a Spaceborne System through the Use of Diode Lasers." Remote Sensing 14, no. 10 (May 18, 2022): 2426. http://dx.doi.org/10.3390/rs14102426.
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Current satellite lidars have sparse spatial coverage, leading to uncertainty from sampling. This complicates robust change detection and does not allow applications that require continuous coverage. One potential way to increase lidar sampling density is to use more efficient lasers. All current spaceborne lidars use solid-state lasers with a limited efficiency of 5–8%. In this paper, we investigate the potential for using diode lasers, with their higher efficiencies, as an alternative. Diode lasers have reported efficiencies of about 25% and are much smaller and lighter than solid-state lasers. However, they can only emit good beam quality at lower peak powers, which has so far prevented them from being used in spaceborne lidar applications. In this paper, we assess whether the novel lidar modalities necessitated by these lower peak powers are suitable for satellite lidar, determined by whether they can match the design performance of GEDI by being able to accurately measure ground elevation through 98% canopy cover, referred to as having “98% beam sensitivity”. Through this, we show that a diode laser can be operated in pulse train or pulse compressed lidar (PCL) mode from space, using a photon-counting detector. In the best case scenario, this setup requires a detected energy of Edet=0.027 fJ to achieve a beam sensitivity of 98%, which is less than the 0.28 fJ required by a full-waveform solid-state lidar instrument, exemplified by GEDI. When also accounting for the higher laser and detector efficiency, the diode laser in pulse train mode requires similar shot energy as a photon counting solid-state laser such as ICESat-2 which along with the higher laser efficiency could result in a doubling of coverage. We conclude that there is a clear opportunity for diode lasers to be used in spaceborne lidars, potentially allowing wider coverage through their higher efficiencies.
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Okamoto, Hajime, Kaori Sato, Masahiro Fujikawa, Eiji Oikawa, Tomoaki Nishizawa, Shoken Ishii, Yoshitaka Jin, Makoto Aoki, and Nobuo Sugimoto. "Development of Synergetic-Active Sensor-System for Evaluation of Observations by Earthcare." EPJ Web of Conferences 237 (2020): 07011. http://dx.doi.org/10.1051/epjconf/202023707011.
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We develop the synergetic ground-based active-sensor-system for the evaluation of observations by space-borne lidars. The system consists of second version of multi-field-view multiple-scattering polarization lidar (MFMSPL-2), multiple-field-of-view high spectral resolution polarization lidar, direct-detection Doppler wind lidar, coherent Doppler wind lidar and 94GHz cloud profiling radar. The system can simulate observed signals from sensors onboard the joint Japanese/European mission Earth Clouds, Aerosols and Radiation Explorer (EarthCARE). The observation system can provide unique opportunity to study interaction of cloud microphysics, aerosol microphysics, vertical air motion and vertical distribution of horizontal wind and it will lead to evaluate cloud-convective parameterization and to reduce uncertainties in climate change predictions.
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Lee, Hyunsuk, and Woojin Chung. "Extrinsic Calibration of Multiple 3D LiDAR Sensors by the Use of Planar Objects." Sensors 22, no. 19 (September 23, 2022): 7234. http://dx.doi.org/10.3390/s22197234.
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Three-dimensional light detection and ranging (LiDAR) sensors have received much attention in the field of autonomous navigation owing to their accurate, robust, and rich geometric information. Autonomous vehicles are typically equipped with multiple 3D LiDARs because there are many commercially available low-cost 3D LiDARs. Extrinsic calibration of multiple LiDAR sensors is essential in order to obtain consistent geometric information. This paper presents a systematic procedure for the extrinsic calibration of multiple 3D LiDAR sensors using plane objects. At least three independent planes are required within the common field of view of the LiDAR sensors. The planes satisfying the condition can easily be found on objects such as the ground, walls, or columns in indoor and outdoor environments. Therefore, the proposed method does not require environmental modifications such as using artificial calibration objects. Multiple LiDARs typically have different viewpoints to reduce blind spots. This situation increases the difficulty of the extrinsic calibration using conventional registration algorithms. We suggest a plane registration method for cases in which correspondences are not known. The entire calibration process can easily be automated using the proposed registration technique. The presented experimental results clearly show that the proposed method generates more accurate extrinsic parameters than conventional point cloud registration methods.
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Fu, Wei, Alessandro Sebastiani, Alfredo Peña, and Jakob Mann. "Influence of nacelle-lidar scanning patterns on inflow turbulence characterization." Journal of Physics: Conference Series 2265, no. 2 (May 1, 2022): 022016. http://dx.doi.org/10.1088/1742-6596/2265/2/022016.
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Abstract Nacelle lidars with different number of beams, scanning configurations and focus distances are simulated for characterizing the inflow turbulence. Lidar measurements are simulated within 100 turbulence wind fields described by the Mann model. The reference wind turbine has a rotor diameter of 52 m. We assume homogeneous frozen turbulence over the lidar scanning area. The lidar-derived Reynolds stresses are computed from a least-square procedure that uses radial velocity variances of each of the beams and compared with those from a simulated sonic anemometer at turbine hub height. Results show that at least six beams, including one beam with a different opening angle, are needed to estimate all Reynolds stresses. Enlarging the beam opening angle improves the accuracy and uncertainty in turbulence estimation more than increasing the number of beams. All simulated lidars can estimate the along-wind variance accurately. This work provides guidance on designing and utilizing nacelle lidars for inflow turbulence characterization.