Pulsed Lidar Research Articles

Research on Pulse Linear Array LiDAR Point Cloud Enhancement Algorithm in Snowy Environment

Abstract LiDAR point cloud data acquisition is difficult in snowfall environment, which leads to fewer point cloud datasets in snowy days and affects the subsequent research on target recognition algorithms in bad weather. In this paper, we investigate a point cloud enhancement algorithm based on pulse linear array LiDAR in snowfall environment. We use a linear array data acquisition method to collect the point cloud data of sunny and snowy days, and the point cloud data of sunny days and different degrees of snowy days are compared. We establish a linear array pulse LiDAR acquisition model and a single-line laser snowfall simulation model. The results show that a large number of snow particles gather in the vicinity of pulse linear array LiDAR and they are conical in distribution. The simulation model can generate point cloud data close to the real snow environment.

Investigation of the three-wave lidar capabilities for monitoring the lower tier forest vegetation

Abstract The possibilities of the three-wave pulsed lidar for monitoring the lower tier of forest vegetation have been studied. The simulation analysis results of the lower tier forest vegetation groups identification on a neural net using measured vegetation spectral reflectance for different wavelengths of the three-wave lidar are presented. It is shown that the best options are lidars with wavelengths 532, 1064, 1570 nm and 532, 1064, 2030 nm. The three-wavelength lidar with these wavelengths allows the identification of five lower tier forest vegetation groups (undergrowth of deciduous trees; undergrowth of coniferous trees; areas of swamps, mosses and shrubby plants; soils with different percentages of vegetation coverage; areas of dry forest, soils without vegetation, lichens, burnt areas) with a probability of correct identification over 0.8 and a probability of incorrect identification under 0.08 (for a relative RMS noise values of 1%).

A probability density functions convolution based analytical detection probability model for LiDAR with pulse peak discriminator

Detection probability as a key indicator of LiDAR determines the quality of 3D images. To explore the detection essence of pulse LiDAR, a probability density function (PDF) convolution based analytical detection probability model is established to predict the detection performance of pulse LiDAR with peak discriminator. In the model, the analytical detection probability is determined by convoluting the PDFs of echo pulse point and the maximum noise amplitude derived from the cumulative multiplication of the PDFs of all noise points. Experiments showed that the theoretical probabilities calculated from model is consistent with the experimental results. Based on the model, a detection threshold of peak discriminator is set to 4.5 times noise standard deviation for achieving a detection probability of 90 %@14.6 dB and a false alarm probability of 0.17 %, which is verified using the lab-built LiDAR. The presented model offers valuable guidance for system design and detection parameter selection.

Quantification and assessment of the atmospheric boundary layer height measured during the AWAKEN experiment by a scanning LiDAR

The atmospheric boundary layer (ABL) height plays a key role in many atmospheric processes as one of the dominant flow length scales. However, a systematic quantification of the ABL height over the entire range of scales (i.e., with periods ranging from one minute to one year) is still lacking in literature. In this work, the ABL height is quantified based on high-resolution measurements collected by a scanning pulsed Doppler LiDAR during the recent American WAKE experimeNt (AWAKEN) campaign. The high availability of ABL height estimates (≈2200 collected over one year and each of them based on 10-min averaged statistics) allows to robustly assess five different ABL height models, i.e., one for convective thermal conditions and four for stable conditions. Thermal condition is quantified by a stability parameter spanning three orders of magnitude and probed by near-ground 3D sonic anemometry. The free-atmosphere stability, quantified by the Brunt–Väisälä frequency, is both calculated from simultaneous radiosonde measurements and obtained from the best fit of two of the chosen ABL height models. Good agreement is found between the data and three of the chosen models, quantified by mean absolute errors on the ABL height between 281 and 585 m. Furthermore, the seasonal variability of the convective ABL height model parameters (−15% to +23% with respect to the year baseline) agrees with the variability of buoyancy-generated turbulence caused by the variation in solar radiation throughout the year.

Modelling polarized pulsed LiDAR signals in scattering media: an approach for optimizing systems in real-world scenarios.

Adverse weather conditions present a primary challenge for ground-based LiDAR imaging systems in outdoor applications. The use of polarization has been proposed as an effective filtering mechanism. However, the number of potential situations is large, complex and difficult to parameterize with accuracy. In such conditions, advanced simulation methods enable the testing of different experimental configurations and the determination of the best possible setup. With this purpose, a Monte Carlo algorithm is presented for modeling polarized pulsed LiDAR signals in turbid media. This algorithm is designed for immediate applicability, incorporating realistic media characterization and accounting for the attributes of existing prototypes. It allows testing various experimental configurations, managing optical obstacles, adjusting polarization arrangements, and different geometries of particles within the medium. The developed algorithm accurately characterizes backscattering signals, revealing their dependence on medium properties. A relationship between visibility and backscattering energy is identified, offering insights for sensor optimization. Polarization analysis highlights the efficacy of circular polarization in mitigating scattering effects and establishes a connection with the polarimetric characteristics of imaged targets. The algorithm's application to irregular particles reveals also an unexpected behavior of polarized light, challenging established strategies. These diverse use cases exemplify the algorithm's capability to model real-world circumstances, emphasizing its significance in predicting cutting-edge situations when designing optical systems for complex and demanding outdoor scenarios.

Reconstructing turbulent wind-fields using inverse-distance-weighting interpolation and measurements from a pulsed mounted-hub lidar

This study evaluates a numerical multi-beam pulsed lidar mounted on the hub of the NREL 5MW reference wind turbine using the HAWC2 v13.1 numerical sensor for synthetic lidar measurement generation. While initially designed for single-beam operations, it facilitates multi-beam configuration simulations. We conducted an analysis of full-rotor longitudinal wind speed reconstruction by combining inverse-distance-weighting with synthetic sensor data from HAWC2. Utilizing a Mann-generated turbulence box for wind input at U = 11.4 m/s, we examined three lidar configurations for efficacy. The hub-mounted lidar proved efficient in capturing the incoming flow towards the turbine, showing a 60% improvement in overall reconstruction accuracy across the plane compared to the baseline, where hublidar measurements are simple average across the rotor plane. The rotor average wind speed showed a 30% enhancement compared to the baseline. Crucially, the lidar configuration, which impacted the spatial distribution across the rotor plane, emerged as a pivotal factor for effective reconstruction. Proper configuration assessment is essential, especially given the implications of rotational sampling and its impact under various wind conditions, for optimal performance. The proposed method, combining inverse-distance weighting with hub-lidar data for high spatial resolution measurements across the rotor plane, shows significant potential for real-time windflow estimation and lidar-assisted control applications.

3D parallel pulsed chaos LiDAR system.

We propose and experimentally demonstrate a parallel pulsed chaos light detection and ranging (LiDAR) system with a high peak power, parallelism, and anti-interference. The system generates chaotic microcombs based on a chip-scale Si3N4 microresonator. After passing through an acousto-optic modulator, the continuous-wave chaotic microcomb can be transformed into a pulsed chaotic microcomb, in which each comb line provides pulsed chaos. Thus, a parallel pulsed chaos signal is generated. Using the parallel pulsed chaos as the transmission signal of LiDAR, we successfully realize a 4-m three-dimensional imaging experiment using a microelectromechanical mirror for laser scanning. The experimental results indicate that the parallel pulsed chaos LiDAR can detect twice as many pixels as direct detection continuous wave parallel chaos LiDAR under a transmission power of -6 dBm, a duty cycle of 25%, and a pulse repetition frequency of 100 kHz. By further increasing the transmission power to 10 dBm, we acquire an 11 cm × 10 cm image of a target scene with a resolution of 30 × 50 pixels. Finally, the anti-jamming ability of the system is evaluated, and the results show that the system can withstand interferences of at least 15 dB.

Target intensity correction method based on incidence angle and distance for a pulsed Lidar system.

Pulsed light detecting and ranging (Lidar) is capable of acquiring comprehensive target information within a single pulse, including distance and intensity data. Intensity data reflects the target's backscattered intensity and is commonly regarded as a crucial observational parameter associated with target reflectivity information. Multiple studies have indicated the potential of intensity data in various applications within pulsed Lidar contexts. However, the intensity data is influenced by the incident angle and distance; hence it cannot directly manifest target characteristics. Consequently, a prerequisite for its usage is the implementation of intensity calibration. This paper presents a target intensity correction method based on an improved tail model, designed for preprocessing intensity data. First, the pulse echo signal equation is derived by incorporating the improved tail model with the detected target. On this foundation, a target echo intensity correction model is established to correct the intensities at various incident angles to those at the normal direction. Lastly, the derived approach is validated through simulation analysis, and practical experiments are conducted on a constructed pulsed Lidar system. These experiments meticulously investigate the influences of incident angle and distance, two prominent factors, on echo intensity. In the context of incident angle correction experiments, the mean absolute errors (MAEs) in calibrated values for diverse targets all remain within 0.04V. Prior to correction, the maximum MAE for the cystosepiment is 0.505V; after the correction it is reduced to merely 0.02V, indicating a 96% reduction in error. Furthermore, all discrepancies exhibit an error standard deviation (ESD) of 0.03V or less, showcasing favorable stability. For distance correction, under normal incidence conditions, a diverse set of targets is measured at different distances to achieve corrected MAE and ESD within 0.05V. Consequently, the proposed method effectively achieves intensity correction concerning incident angles and distances. To achieve this, a reflectivity lookup table for the relevant targets was established. Combining this with the corrected intensity information enabled target identification in the three-dimensional imaging of pulsed Lidar.

Comparison of timing discrimination method for pulse-based Lidar

Time discrimination methods of pulse signals serve as the foundation for ranging, identification, and precision in pulse Lidar. Therefore, employing a judicious time discrimination method is pivotal in enhancing Lidar overall performance. This study initially delves into the theoretical distinctions among various time discrimination methods, including constant fraction timing, waveform centroid, dual-threshold waveform, and amplitude with rising edge compensation timing. It meticulously analyzes and compares these diverse methods for time discrimination. Subsequently, employing these methodologies to process Lidar echo signals to contrast their time measurement accuracy. The conclusions will provide valuable guidance for the design and practical application of pulse-type Lidar systems.

Geometrical and optical properties of cirrus clouds in Barcelona, Spain: analysis with the two-way transmittance method of 4 years of lidar measurements

Abstract. In this paper a statistical study of cirrus geometrical and optical properties based on 4 years of continuous ground-based lidar measurements with the Barcelona (Spain) Micro Pulse Lidar (MPL) is analysed. First, a review of the literature on the two-way transmittance method is presented. This method is a well-known lidar inversion method used to retrieve the optical properties of an aerosol–cloud layer between two molecular (i.e. aerosol and cloud-free) regions below and above, without the need to make any a priori assumptions about their optical and/or microphysical properties. Second, a simple mathematical expression of the two-way transmittance method is proposed for both ground-based and spaceborne lidar systems. This approach of the method allows the retrieval of the cloud optical depth, the cloud column lidar ratio and the vertical profile of the cloud backscatter coefficient. The method is illustrated for a cirrus cloud using measurements from the ground-based MPL and from the spaceborne Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). Third, the database is then filtered with a cirrus identification criterion based on (and compared to) the literature using only lidar and radiosonde data. During the period from November 2018 to September 2022, 367 high-altitude cirrus clouds were identified at 00:00 and 12:00 UTC, of which 203 were successfully inverted with the two-way transmittance method. The statistical results of these 203 high-altitude cirrus clouds show that the cloud thickness is 1.8 ± 1.1 km, the mid-cloud temperature is −51 ± 8 ∘C and the linear cloud depolarization ratio is 0.32 ± 0.13. The application of the transmittance method yields an average cloud optical depth (COD) of 0.36 ± 0.45 and a mean effective column lidar ratio of 30 ± 19 sr. Statistical results of the errors associated with the two-way transmittance method retrievals are also provided. The highest occurrence of cirrus is observed in spring and the majority of cirrus clouds (48 %) are visible (0.03 < COD < 0.3), followed by opaque (COD > 0.3) with a percentage of 38 %. Together with results from other sites, possible latitudinal dependencies have been analysed together with correlations between cirrus cloud properties. For example, we noted that in Barcelona the COD correlates positively with the cloud base temperature, effective column lidar ratio and linear cloud depolarization ratio and negatively with the cloud base height.

Comparative Analysis of Aerosol Vertical Characteristics over the North China Plain Based on Multi-Source Observation Data

In this paper, multi-source observation, such as aircraft, ground-based remote sensing, and satellite-retrieved data, has been utilized to compare and analyze the vertical characteristics of aerosol optical properties and the planetary boundary layer height (HPBL) over the North China Plain (NCP) region during May–June 2016. Aircraft observations show the vertical profiles of aerosol absorption coefficients (σabs), scattering coefficients (σsca), and extinction coefficients (σext) gradually decrease with altitude, with their maximum values near HPBL. The vertical profiles of σext depended most on the vertical distribution of measured σsca, indicating a significant contribution of scattering aerosols. In addition, the prominent characteristic of the inverse relationship between σext and moisture profile could serve as a reference for predicting air quality in the NCP region. The lower layer pollution during the field experiment was likely caused by the accumulation of fine-mode aerosols, characterized by the vertical distribution of the Ångström exponent and the Aerosol Robotic Network (AERONET) products. Typically, HPBL derived from aircraft and surface Micro Pulse Lidar (MPL) was approximate, while the predicted HPBL by meteorological data indicates an underestimation of ~192 m. Aerosol optical depth (AOD) calculated from aircraft and ground-based remote sensing (such as MPL and AERONET) experienced a strong correlation, and both of them exhibited a similar tendency. However, the AOD retrieved from satellites was significantly larger than that from aircraft and ground-based remote sensing. Overall, the inversion algorithm, cloud identification algorithm, representativeness of the space, and time of the observation may lead to an overestimation or underestimation of AOD under certain circumstances. This study may serve as a re-evaluation of AOD retrieved from multi-source observations and provide a reference to uncover the actual atmospheric environment in the NCP regions.

Robust Multi-Event Detection for Pulsed LiDARs

Robust Multi-Event Detection for Pulsed LiDARs

Feedforward pitch control for a 15 MW wind turbine using a spinner-mounted single-beam lidar

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.

Research on applying scan matching algorithm to improve velocity measurement accuracy of single-line ranging lidar

There has been increased demand for safe and efficient speed measurement of moving objects in engineering and practical applications, particularly in scenarios involving the measurement of the movement speed of objects at close range. Thus, this study designed a single-line scanning pulsed lidar system. In addition, algorithms were employed to enhance the measurement accuracy of the single-line ranging pulsed lidar. In this study, the lidar was installed on a guideway-integrated testing platform to obtain point cloud data, which was processed using the normal distributions transform (NDT), iterative closest points (ICP), and correlative scan matching (CSM) algorithms. The experimental results demonstrated that the NDT algorithm outperformed the ICP and CSM algorithms in terms of velocity measurement accuracy and algorithm robustness. Moreover, the velocity measurement results obtained from the NDT algorithm were closer to the actual track speed, with a maximum velocity deviation of lesser than 0.021 m/s compared to the actual guideway speed.

Denoising complex background radar signals based on wavelet decomposition thresholding

Abstract The echo signals of the radar in complex backgrounds are often very unstable and thus require effective noise cancellation. In this paper, according to the characteristics of continuous wavelet variation and discrete wavelet variation, the decomposition effect of multi-resolution analysis and orthogonal Mallat algorithm on low-frequency and high-frequency non-smooth signals is studied, and the selection method of wavelet bases is explored. Then, the noise characteristics affecting the pulsed LIDAR system are analyzed, and the LIDAR pulse signal is simulated by MATLAB, while Gaussian white noise is introduced to obtain the noise-added echo signal, and then multiple wavelet threshold denoising methods are applied to denoise the echo signal. For the input signal-to-noise ratio of −10.57 dB, the output signal-to-noise ratios of db8, db9, db10, and bior3.5 wavelet bases under forced thresholding are −1.971, −2.178, −2.173, and −1.032, respectively. For different input signal-to-noise ratios, the average root mean square error of db8, db9, db10, and bior3.5 wavelet bases under default thresholding is 1.51. The denoising methods for radar signals using the properties of wavelet decomposition have obvious superiority compared to traditional filters, and the wavelet transforms threshold denoising methods have wide adaptability.

A Pulsed Lidar System With Ultimate Quantum Range Accuracy

A light detection and ranging (lidar) system using a multi-output quantum pulse gate (mQPG) for quantum uncertainty limited range resolution is presented. Due to the inherent phase-sensitivity of the process, the proposed mQPG enhanced lidar system is able to beat the theoretical Rayleigh range resolution limit and the single detection Craméer-Rao bound (CRB) of classic pulsed lidar. To achieve this behavior, gating pulses interact with the backscattered lidar pulse while propagating through the optically non linear waveguide within the mQPG. The intensity of the discrete spectral channels of the mQPG contains finally the target distance informations. The mQPG was fabricated in a periodically poled (PP) titanium-indiffused lithium niobate waveguide and the entire system was built up in a lab environment. Measurement up to 1500 μm were performed around an arbitrary set reference point, and show excellent agreement with the theory up to 600 μm for a pulse length of 1.56ps, and up to 1100 μm for a pulse length of 2.12ps.

Research on echo characteristics in remote detection with the pulse LiDAR of aerial targets under diverse atmospheric conditions

This paper utilizes the idea of theoretical analysis to introduce a method for echo characteristics in remote detection with the pulse LiDAR of aerial targets under atmospheric conditions. A Missiles and an aircraft are selected as simulation targets. The relation among mutual mapping of target surface elements can be directly gained by setting light source and target parameters. We discuss influences on atmospheric transport conditions, target shapes and detection conditions on echo characteristics. Atmospheric transport model is introduced as weather conditions, including sunny and cloudy days, with or without turbulence. Simulation results conclude that the outline of scanned waveform can invert the target shape. These provide a theoretical basis for improving the target detection and tracking performance.

Remote Polar Boundary Layer Wind Profiling Using an All-Fiber Pulsed Coherent Doppler Lidar at Zhongshan Station, Antarctica

A compact all-fiber pulsed coherent Doppler lidar (PCDL) for boundary layer wind measurement was developed by the Institute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences). It has been deployed at Zhongshan Station (69.4° S, 76.4° E) during the 2020 austral summer season by the 36th Chinese National Antarctic Research Expedition (CHINARE) and started routine observation in January 2020. This system, based on the 1550 nm all-fiber components, employs a 100 mm telescope with a long focal length of 632.6 mm to emit and collect laser pulses. It provides the ability to measure vertically resolved wind fields with a spatial resolution of 30 m and a temporal resolution of 1 min; the maximum detection range is up to 1.5 km in Antarctica. Wind speed and direction inversion methods were introduced subsequently. Preliminary measurement results of wind profiles indicate that this Doppler lidar can be operated successfully in Antarctica. The synchronous observations between the lidar, anemometer, and radiosondes at Zhongshan station are presented and have good consistency with each other. The comparison results between the lidar and anemometer indicate a root mean square deviation (RMSD) of 0.98 m s−1 and 10.55° for wind speed and direction, respectively. The lidar continuous observations of wind profiles provide an opportunity to study the spatiotemporal variation of Antarctic wind with high resolutions, which is useful for further understanding of the atmosphere in Antarctic regions.

Influence of phenology on waveform features in deciduous and coniferous trees in airborne LiDAR

Information on forest structure is vital for sustainable forest management. Currently, airborne LiDAR remote sensing has been well established as an effective tool to characterize the structure of canopies and forest inventory variables. Radiometry and geometry are highly intertwined in LiDAR remote sensing of forest vegetation and phenology influences the geometric-optical properties of deciduous and evergreen trees causing seasonal variation in LiDAR observations. This variation may be considered as a nuisance or exploited in for example tree species identification. Airborne LiDAR data are also influenced by sensor functioning, acquisition settings, scan geometry and the atmosphere. Reliable estimation of subtle phenological effects calls for data in which the impact of the external factors is minimal. We experimented with such data and explored LIDAR waveforms (WFs) in boreal trees in winter, early summer and late summer. Our objectives were to i) assess the match of the multitemporal LiDAR data for observing true changes in vegetation; ii) quantify the influence of phenology in deciduous and evergreen trees; iii) study the effect of varying scan zenith angle (SZA) and canopy age on WF features in different phenostates; iv) assess the temporal feature correlation in individual living and dead standing trees. A WF-recording pulsed LiDAR sensor unit operating at the wavelength of 1550 nm was used in repeated acquisitions. WF attributes such as energy, peak amplitude and echo width were derived for each pulse and were localized vertically to crown, understory and ground components. Silver and downy birch, black alder, European aspen, Siberian larch, Scots pine, Norway spruce and dead standing spruce formed our strata. Results showed that phenology caused more variation in WF features of deciduous trees compared to evergreen conifers. Deciduous trees displayed substantial between-species variation that was linked with differences in branching pattern, leaf orientation and bark reflectance. Pine displayed a possible winter-early summer anomaly in canopy backscattering that may be linked with changes in foliage clumping or with the role of stamens in early summer trees. Trees displayed positive temporal correlation in WF features and correlations were the strongest in evergreen and deciduous conifers and decreased with time. SZA had minor influence on WF features whereas age exercised a strong effect on many features with parallel variation between species and phenostates. Structural changes following death, i.e. ‘aging’ changed the geometric WF features of dead standing trees. Our results provide new insights for enhancing tree species identification by using WF LiDAR and for LiDAR time-series analysis of vegetation.

Improving the ranging performance of chaos LiDAR.

Chaos lidar has gained significant attention due to its high spatial resolution, natural anti-interference capability, and confidentiality. However, constrained by the power of the chaos laser, the sensitivity of the linear detector, and the hardware bandwidth, chaos lidar is greatly restricted in the application of long-distance target detection and imaging. To overcome these constraints, we propose a novel, to the best of our knowledge, chaos lidar based on Geiger mode avalanched photodetectors (GM-APDs) in a previous study called chaos single-photon (CSP) lidar. In this paper, we compare the CSP lidar with the linear mode chaos lidars by combining with lidar equation. Regarding the ranging principle, the CSP lidar is fully digital and breaks through the constraints of a detector's bandwidth and ADC's sampling rate. The simulation results indicate that the detection range of the CSP lidar is approximately 35 times and 8 times greater than that of a continuous-wave chaos lidar and pulsed chaos lidar, respectively. Although the detection accuracy of the CSP lidar is only at the centimeter level and is lower than the linear mode chaos lidars, its consumption of storage resources and power is greatly reduced due to 1-bit quantization in the GM-APD. Additionally, we investigate the impact of GM-APD parameters on the signal-to-noise ratio (SNR) of the CSP lidar system and demonstrate that the dead time difference between GM-APDs has a negligible effect. In conclusion, we present and demonstrate a new chaos lidar system with a large detection range, high SNR, low storage resources and power consumption, and on-chip capability.