Doppler Light Detection And Ranging Research Articles

Advancements in Sensor Fusion for Underwater SLAM: A Review on Enhanced Navigation and Environmental Perception

Underwater simultaneous localization and mapping (SLAM) has significant challenges due to the complexities of underwater environments, marked by limited visibility, variable conditions, and restricted global positioning system (GPS) availability. This study provides a comprehensive analysis of sensor fusion techniques in underwater SLAM, highlighting the amalgamation of proprioceptive and exteroceptive sensors to improve UUV navigational accuracy and system resilience. Essential sensor applications, including inertial measurement units (IMUs), Doppler velocity logs (DVLs), cameras, sonar, and LiDAR (light detection and ranging), are examined for their contributions to navigation and perception. Fusion methodologies, such as Kalman filters, particle filters, and graph-based SLAM, are evaluated for their benefits, limitations, and computational demands. Additionally, innovative technologies like quantum sensors and AI-driven filtering techniques are examined for their potential to enhance SLAM precision and adaptability. Case studies demonstrate practical applications, analyzing the compromises between accuracy, computational requirements, and adaptability to environmental changes. This paper proceeds to emphasize future directions, stressing the need for advanced filtering and machine learning to address sensor drift, noise, and environmental unpredictability, hence improving autonomous underwater navigation through reliable sensor fusion.

Wind Profile Reconstruction Based on Convolutional Neural Network for Incoherent Doppler Wind LiDAR

The rapid development of artificial intelligence (AI) and deep learning has revolutionized the field of data analysis in recent years, including signal data acquired by remote sensors. Light Detection and Ranging (LiDAR) technology is widely used in atmospheric research for measuring various atmospheric parameters. Wind measurement using LiDAR data has traditionally relied on the spectral centroid (SC) algorithm. However, this approach has limitations in handling LiDAR data, particularly in low signal-to-noise ratio (SNR) regions. To overcome these limitations, this study leverages the capabilities of customized deep-learning techniques to achieve accurate wind profile reconstruction. The study uses datasets obtained from the European Centre for Medium Weather Forecasting (ECMWF) Reanalysis v5 (ERA5) and the mobile Incoherent Doppler LiDAR (ICDL) system constructed by the University of Science and Technology of China. We present a simulation-based approach for generating wind profiles from the statistical data and the associated theoretical calculations. Whereafter, our team constructed a convolutional neural network (CNN) model based on the U-Net architecture to replace the SC algorithm for LiDAR data post-processing. The CNN-generated results are evaluated and compared with the SC results and the ERA5 data. This study highlights the potential of deep learning-based techniques in atmospheric research and their ability to provide more accurate and reliable results.

Explainable Boosting Machine: A Contemporary Glass-Box Strategy for the Assessment of Wind Shear Severity in the Runway Vicinity Based on the Doppler Light Detection and Ranging Data

Pilots commonly undergo training to effectively manage instances of wind shear (WS) during both the landing and takeoff stages. Nevertheless, in exceptional circumstances, there may be instances of severe wind shear (SWS) surpassing a magnitude of 30 knots, leading to adverse effects on the operation of taking off and landing aircraft. This phenomenon can lead to the execution of aborted landing maneuvers and deviations from the intended glide path. This study utilized the explainable boosting machine (EBM), an advanced machine learning (ML) model known for its transparency, to predict the severity of WS occurrences and analyze the underlying factors. The dataset consisted of 21,392 data points from 2018 to 2022 acquired from two Doppler light detection and ranging (LiDAR) systems installed at Hong Kong International Airport (HKIA). Initially, the Doppler LiDAR data received data treatment in order to address the issue of data imbalance. Subsequently, utilizing the processed data, the hyperparameters of EBM were optimized using the Bayesian optimization technique. The EBM model underwent subsequent training and evaluation, wherein its performance metrics were computed and compared with those of an alternative glass-box model including decision tree (DT) and counterpart black-box models, namely, random forest (RF) and extreme gradient boosting (XGBoost). The EBM model trained on synthetic minority oversampling technique (SMOTE)-treated data demonstrated superior performance in comparison with the alternative models, as indicated by its higher geometric mean (0.77), balanced accuracy (0.78), and Matthews’ correlation coefficient (0.169). Furthermore, the EBM exhibited enhanced predictive performance and facilitated a comprehensive analysis of individual and pairwise factor interactions in the prediction of WS severity. This enabled the assessment of the factors that contributed to the instances of SWS in the proximity of airport runways.

Doppler Light Detection and Ranging-Aided Inertial Navigation and Trajectory Recovery

A sensor fusion approach to terrain relative navigation is proposed in this paper. Sensor data from Global Position System (GPS), Inertial Navigation System (INS), and Doppler light detection and ranging (LIDAR) provide a relative state estimate through a novel multiplicative extended Kalman filter. The measurement model of the Doppler LIDAR is derived from first principals and employed by the filter to update the estimates propagated by the GPS/INS data stream. The line-of-sight Doppler velocity measurement provides direct feedback to the velocity states and improves sensitivity to these state estimates. A novel Rauch–Tung–Striebel smoother framework is derived that is compatible with states exhibiting multiplicative error that enables seamless postprocessing of state estimates filtered with a multiplicative extended Kalman filter. This new filter and smoother framework is tested with suborbital flight data from Blue Origin’s New Sheppard ascent and landing missions.

Doppler velocimeter and vibrometer FMCW LiDAR with Si photonic crystal beam scanner.

In this paper, we propose and demonstrate a frequency-modulated continuous-wave light detection and ranging (LiDAR) with a Si photonic crystal beam scanner, simultaneously enabling scanning laser Doppler measurements. This nonmechanical solid-state device can reduce the size of conventional scanning laser Doppler vibrometers, making LiDAR a multimodal imaging sensor, which can measure the distributions of distance, velocity, and vibration frequency. We fabricated this device using Si photonics process and confirmed the expected operations. Distance and velocity resolutions were less than 15 mm and 19 mm/s, respectively. The detection limit of the vibration amplitude determined by the signal-to-noise ratio was 2.5 nm.

Influence of a weak typhoon on the vertical distribution of air pollution in Hong Kong: A perspective from a Doppler LiDAR network

High particulate matter (PM) and ozone (O3) concentration in Hong Kong are frequently observed during the summertime typhoon season. Despite the critical effect of a typhoon on air pollution, contributions of vertical wind profile and cloud movement during transboundary air pollution (TAP) on surface PM and O3 concentration have yet to be fully understood. This work is the first study to apply a network of Doppler light detection and ranging (LiDAR) as well as back trajectory analysis to comprehensively analyze the effect of a weak Typhoon (Danas) occurring during 16-19 July 2019 on different variations in PM and O3 concentration. During the typhoon Danas, three types of surface air pollution with five episodes were identified: (1) low PM and high O3 concentration; (2) co-occurring high PM and O3 concentration and (3) high PM and low O3 concentration. Employing our 3D Real-Time Atmospheric Monitoring System (3DREAMs) along with surface observations, we found the important role of TAP in the increases in surface PM and O3 concentration with significant vertical wind shear that transported air pollutants at upper levels, and strong vertical mixing that brought air pollutants to the ground level. Cloud movement related to typhoon periphery, as well as high solar radiation due to sinking motion and remote transport by continental wind, have an impact on local O3 concentration. For the substantial difference in O3 concentration between two air quality measurement sites, the similar vertical aerosol distributions and wind profiles suggest the comparable TAP contributions at the two sites and thus infer the critical role of local O3 photochemical process in the O3 difference. This work comprehensively reveals the influences of a weak typhoon on variations in PM and O3 during the five episodes, providing important references for air quality monitoring and forecast in regions under the influence of typhoon.

Fast dual‐doppler LiDAR retrieval of boundary layer wind profiles

Operational doppler LiDARs (light detection and ranging) are often heavily engaged in specialised phenomenon detection, as well as dedicated surveillance scans, leaving little room for further additions to the tightly packed scanning strategy. This paper presents a fast method for retrieval of the urban boundary layer wind profile using existing scan data from two long-range doppler LiDARs at the Hong Kong International Airport (HKIA). Leveraging occasional range height indicator scans originally designed to aid the monitoring of terrain-induced wind disturbances, vertical profiles of the horizontal winds between 150 and 750m above ground level are estimated near the intersection point. The LiDAR-derived wind profiles are validated against measurements from a nearby wind profiler, as well as Aircraft Meteorological Data Relay (AMDAR) flight observations, for a 1-year period, 2019. Results indicated close agreement in terms of wind speed and direction between the LiDAR-derived profiles and wind profiler measurements, particularly above 300m. A slant angle correction factor is found to effectively alleviate the underestimation of the horizontal wind components at higher beam angles while also improving the consistency of the retrieved wind speed profile across different altitudes. For the AMDAR comparison, large discrepancies in wind speed and direction might be attributed to the natural variability of glide path winds well-known to HKIA. This study demonstrates the potential of extracting additional boundary layer wind information from ‘part-time’ scans of operational doppler LiDARs.

Onboard wake vortex localization with a coherent 1.5 µm Doppler LIDAR for aircraft in formation flight configuration.

An onboard LIght Detection And Ranging (LIDAR) sensor designed to track wake vortex created by aircraft in formation flight is presented. It uses short pulses (75 ns) to obtain a spatial resolution of ∼22.5 m required to resolve small-scale structures of vortices and a blind zone of 17.5 m to locate vortices next to the wing tip. Monte Carlo simulations show that vortex centers could be located within ±0.5 m. Flight tests were performed with two aircraft in formation flight configuration. The LIDAR, installed in the following aircraft, was able to measure, in real time (every 6 s), the air flow velocities induced by the vortices created by the leading aircraft. The software was used to determine the vortex centers. These measurements were coupled to global positioning system (GPS) measurements of the two aircraft positions to determine the falling velocity of the vortices and infer their circulations.

Reconstruction of Three-Dimensional Dynamic Wind-Turbine Wake Wind Fields with Volumetric Long-Range Wind Doppler LiDAR Measurements

This paper presents a method for reconstructing the wake wind field of a wind turbine based on planar light detection and ranging (LiDAR) scans crossing the wake transversally in the vertical and horizontal directions. Volumetric measurements enable the study of wake characteristics in these two directions. Due to a lack of highly resolved wind speed measurements as reference data, we evaluate the reconstruction in a synthetic environment and determine the reconstruction errors. The wake flow of a multi-megawatt wind turbine is calculated within a 10-min large-eddy simulation (LES) for high-thrust loading conditions. We apply a numerical LiDAR simulator to this wake wind field to achieve realistic one-dimensional velocity data. We perform a nacelle-based set-up with combined plan position indicator and range height indicator scans with eight scanning velocities each. We temporally up-sample the synthetic LiDAR data with a weighted combination of forward- and backward-oriented space–time conversion to retrospectively extract high-resolution wake characteristic dynamics. These dynamics are used to create a dynamic volumetric wake deficit. Finally, we reconstruct the dynamic wake wind field in three spatial dimensions by superposing an ambient wind field with the dynamic volumetric wake deficit. These results demonstrate the feasibility of wake field reconstruction using long-range LiDAR measurements.

A Review of Progress and Applications of Pulsed Doppler Wind LiDARs

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.

Gust Alleviation Control using Prior Gust Information: Wind Tunnel Test Results

Abstract This paper reports dynamic wind tunnel test results of gust alleviation using preview control. The wind tunnel tests are conducted as a part of validation of gust alleviation control using an onboard Doppler LIDAR (Light Detection and Ranging) system, which was developed by JAXA (Japan Aerospace Exploration Agency) and can measure wind velocities in front of an aircraft. The wind tunnel system is composed of a gust wind generator, a half-span rigid aircraft model, a model support system and a digital controller unit. The aircraft model is allowed to move pitch direction by the support system. It is equipped with two control surfaces, which are controlled by commands from the controller unit. Since the LIDAR system cannot be used in the wind tunnel system, the LIDAR information is emulated using the predetermined timeseries of the gust wind generator and used for the preview control law. The wind tunnel tests are conducted with 1-cosine shape gust generation commands and the proposed preview control law is compared with a conventional feedback control law. The results show that the proposed control law is effective in alleviating vertical load caused by gust wind.

Effect of Land-Use Change on the Urban Heat Island in the Fukuoka–Kitakyushu Metropolitan Area, Japan

In coastal cities, the effect of the sea breeze in mitigating the urban heat island (UHI) phenomenon has attracted attention. This study targeted the Fukuoka–Kitakyushu metropolitan area, the fourth largest metropolitan area in Japan which is also coastal. Doppler Light Detection And Ranging (LiDAR) observations were conducted in the summer of 2015 to clarify the transition of the wind field over the targeted area. To investigate the effects on the UHI of land-use change related to urbanization, the National Land Numerical Information (NLNI) land-use datasets for Japan in 1976 (NLNI-76) and 2009 (NLNI-09) were used in the Weather Research and Forecasting (WRF) model. The results of the simulation showed that most of the northern part of the Kyushu region became warmer, with an average increase of +0.236 °C for the whole simulation period. Comparing the two simulations and the Doppler LiDAR observations, the simulation results with the NLNI-09 dataset (for the year closest to the study period in 2015) showed closer conformity with the observations. The results of the simulation using NLNI-76 showed faster sea breeze penetration and higher wind velocity than the observations. These results suggest that the land-use change related to urbanization weakened the sea breeze penetration in this area.

Application of LIDAR technology for rail surface monitoring and quality indexing

This paper investigates the application of Doppler Light Detection and Ranging (LIDAR) sensors for the assessment of the top of rail lubricity condition and layer material. Different top of rail conditions are distinguished by the system using a new pair of rail surface indices defined based on LIDAR measurements. These indices provide quantitative representations of the top of rail condition due to the fact that Doppler frequency range and spectral magnitude of a backscattered LIDAR beam are functions of the rail surface figure as well as the light absorption properties of the surface material. Laboratory tests are conducted to demonstrate the feasibility of the proposed top of rail indexing operation. The results indicate that LIDAR sensors are capable of detecting and distinguishing between different top of rail surface conditions. Instrumenting rail inspection vehicles with Doppler LIDAR systems reduces reliance on empirical top of rail lubricity and surface assessments (such as observing the sheen of the rail or tactilely sensing various residues on the rail), in favor of reliable and repeatable measurements.

Railway track irregularity and curvature estimation using doppler LIDAR fiber optics

The application of Doppler-based LIght Detection and Ranging (LIDAR) technology for determining track curvature and lateral irregularities, including alignment and gage variation, are investigated. The proposed method uses track measurements by two low-elevation, slightly tilted LIDAR sensors nominally pointed at the rail gage face on each track. The Doppler LIDAR lenses are installed with a slight forward angle to measure track speed in both longitudinal and lateral directions. The lateral speed measurements are processed for assessing the track gage and alignment variations, using a method that is based on the frequency bandwidth dissimilarities between the vehicle speed and track geometry irregularity. Using the results from an extensive series of tests with a body-mounted Doppler LIDAR system on-board a track geometry measurement railcar, the study indicates a close match between the LIDAR measurements and those made with existing sensors on-board the railcar. The field testing conducted during this study indicates that LIDAR sensors could provide a reliable, non-contact track monitoring instrument for field use in various weather and track conditions, potentially in a semi-autonomous or autonomous manner.

Lidar Uncertainty Measurement Experiment (LUMEX) – Understanding Sampling Errors

Coherent Doppler LIDAR (Light Detection and Ranging) has been widely used to provide measurements of several boundary layer parameters such as profiles of wind speed, wind direction, vertical velocity statistics, mixing layer heights and turbulent kinetic energy (TKE). An important aspect of providing this wide range of meteorological data is to properly characterize the uncertainty associated with these measurements.With the above intent in mind, the Lidar Uncertainty Measurement Experiment (LUMEX) was conducted at Erie, Colorado during the period June 23 rd to July 13 th , 2014. The major goals of this experiment were the following: Characterize sampling error for vertical velocity statistics Analyze sensitivities of different Doppler lidar systems Compare various single and dual Doppler retrieval techniques Characterize error of spatial representativeness for separation distances up to 3 km Validate turbulence analysis techniques and retrievals from Doppler lidars This experiment brought together 5 Doppler lidars, both commercial and research grade, for a period of three weeks for a comprehensive intercomparison study. The Doppler lidars were deployed at the Boulder Atmospheric Observatory (BAO) site in Erie, site of a 300 m meteorological tower. This tower was instrumented with six sonic anemometers at levels from 50 m to 300 m with 50 m vertical spacing.A brief overview of the experiment outline and deployment will be presented. Results from the sampling error analysis and its implications on scanning strategy will be discussed.

Model Predictive Flight Controller Using Prior Air Disturbance Information Obtained by Doppler LIDAR

In the aviation industry, microburst wind shear is considered to be a major safety threat, especially in some crucial phases of flight like takeoff and landing. Recently, the air speed sensor called Doppler LIDAR (Light Detection and Ranging) which measures the speed of air disturbance even Clear Air Turbulences (CAT) in front of the aircraft is developed. In order to utilize measurement data of Doppler LIDAR, we design the model predictive flight controller to avoid accidents caused by microburst wind shear in the landing configuration assuming the prior information would be obtained by Doppler LIDAR. The effectiveness of the proposed controller, numerical simulations are carried out, in which the plant uncertainties in the aircraft states and the measurement errors in the prior disturbance information are considered.

2305 事前乱気流情報及びモデル予測制御を用いたマイクロバースト下での着陸アプローチのための飛行制御(OS3-2 航空機の制御,OS3 交通・物流システムの制御,オーガナイズド・セッション(OS))

In the aviation industry, microburst wind shear is considered to be a major safety threat, especially in some crucial phases of flight like take-off and landing. Recently, the air speed sensor called airborne Doppler LIDAR (Light Detection and Ranging) which measures the speed of air disturbance even Clear Air Turbulences (CAT) in front of the aircraft is developed. Therefore we design the model predictive flight controller to avoid accidents caused by microburst in the landing configuration assuming the prior turbulence information would be obtained by the LIDAR. To assess the tracking performance of the proposed controller, numerical simulations are carried out, in which the plant uncertainties in the aircraft states and the measurement errors in the prior turbulence information are considered. In addition, the calculation time for the optimization process in model predictive control is examined to confirm that our controller could be utilized in the on-line system.

On-board axial detection of wake vortices using a 2-m m LiDAR

This paper describes the first successful attempt to detect wake vortices axially using an on-board infrared pulsed Doppler LiDAR (light detection and ranging) is described. On-board axial detection is more complex than the classic ground-based tangential approach, because the axial air speed in vortices is low and the atmospheric particle density is reduced, yielding a poorer SNR. To provide meaningful results in such unfavorable conditions we have developed a new flexible signal processing method based on a two-primitive model fitting the spectrum of the Doppler return. This new spectral estimation successfully detects wake vortices with an admissible SNR that is lower than other on-board state-of-the-art approaches. It was validated through flight tests.

Depiction of complex airflow near Hong Kong International Airport using a Doppler LIDAR with a two-dimensional wind retrieval technique

The Hong Kong Observatory (HKO) operates a Doppler Light Detection And Ranging (LIDAR) system at the Hong Kong International Airport (HKIA) to monitor the airflow around the airport area. The LIDAR measures the radial component of the wind field. To better visualize the airflow, a variational method which has been successfully applied to Doppler Radar data is adopted in this study to retrieve the two-dimensional wind field based on the LIDAR measurements. The wind field so obtained is found to reveal many salient features of terrain-induced airflow disturbances at HKIA, such as mountain waves and vortices. Its application to the detection of low-level windshear is demonstrated through selected cases. With a simple extension of the variational method, dual-Doppler analysis is also carried out using the radial velocity data from both the LIDAR and a Terminal Doppler Weather Radar (TDWR) to retrieve the wind field at the airport area in a gust front event.

2 μm LIDAR for laser-based remote sensing: flight demonstration and application survey

A flight test of a diode-pumped solid-state 2 /spl mu/m Doppler Light Detection And Ranging (LIDAR) system was conducted on-board the NASA Ames DC-8 Airborne Laboratory. This was the first ever airborne demonstration of a 2 /spl mu/m diode-pumped solid-state Doppler LIDAR. The LIDAR performance was verified by comparing the true-airspeed (TAS) estimate with that found using the pneumatic air data system; excellent agreement was found. The capabilities of this pulsed 2 /spl mu/m Doppler LIDAR system include high bandwidth air data determination without the need for extensive forebody calibration, remote wind profiling as far as several kilometers away from the aircraft, eye-safe laser transmission at 2 /spl mu/m, and diode-pumped solid-state design for compact construction and reliable performance. >