Pulsed Lidar Research Articles

A Cross-Correlation-Based Time-of-Flight Design for Pulsed Chaos Lidar Systems

A Cross-Correlation-Based Time-of-Flight Design for Pulsed Chaos Lidar Systems

Smoothed accumulated spectra based wDSWF method for real-time wind vector estimation of pulsed coherent Doppler lidar.

Wind vector estimation method with high accuracy in the low signal-to-noise ratio region improves the performance of pulsed coherent Doppler lidar. The key to improving accuracy is to process the incorrect radial wind estimates or the distorted power spectra better. The smoothed accumulated spectra based weighted sine wave fitting method proposed here minimizes the effects of bad radial wind estimates by considering both signal intensity and wind spatial continuity. Leveraging spatial continuity from smoothed accumulated spectra, the weight coefficients and real-time wind vector profiles can be quickly determined with non-looped operations. Simulations and field experiments showed that the proposed method provides comparable or even slightly better quality and more available wind vector estimates than the filtered sine wave fitting method.

Impact of near-surface turbulence on PM2.5 concentration in Chengdu during the COVID-19 pandemic

The role of meteorological conditions has long been recognized in modulating regional air quality. The impact of near-surface turbulence, nevertheless, remains poorly understood. To curb the spread of COVID-19, a variety of lockdown measures were implemented, providing us an unprecedented opportunity to examine the joint impact of emission control and meteorology on regional air quality. Here we examined the variations of planetary boundary layer (PBL) height, PM2.5 concentrations, turbulence kinetic energy (TKE), vertical wind shear, and their associations in Chengdu, Sichuan province in Southwest China between January 13 and February 24, 2020, by synergistically using micro pulse lidar, ground-level meteorological and PM2.5 measurements, as well as ultrasonic anemometer observations. During the study period, Sichuan basin was primarily regulated by the straight west wind, with an averaged wind speed of 2–3 m/s at 850 hPa, indicative of a relatively stable atmospheric dispersion condition. TKE was positively correlated with PBL height but negatively correlated with PM2.5. The PM2.5 concentration varied dramatically during pre- and post-lockdown periods but remained near constant at a relatively low level during the lockdown period. Meanwhile, the negative correlation between TKE and PM2.5 was much stronger during the lockdown and post-lockdown periods, when aerosol emissions were significantly reduced. Moreover, the correlation between TKE and PM2.5 exhibited large diurnal variability, with the strongest correlation observed during the daytime when solar radiation and turbulent mixing generally reached their peaks. Overall, the observational results in Chengdu underscore the non-negligible impact of turbulence on regional PM2.5 concentrations, which could help better understand the variation of regional air pollution events.

Correction algorithm of the frequency-modulated continuous-wave LIDAR ranging system.

Frequency-modulated continuous-wave LIDAR has broad application prospects. Compared with the traditional pulse LIDAR, the FMCW LIDAR has the advantages of high resolution and long measurement distance. But it still can be affected by several factors, including environmental noise, spectrum aliasing, spectrum leakage and other issues. Some traditional filtering algorithms or signal transformation algorithms can improve the above problems, but the effect is not ideal. This paper proposes a signal correction algorithm called the VMD-based refined cross-power spectral density algorithm (VRCPSD). This algorithm is based on signal decomposition denoising and improved spectrum refinement methods. The algorithm applies variational mode decomposition, spectrum refinement and cross-power spectral density to signal processing. The VRCPSD algorithm is compared with the traditional spectrum correction algorithm on the high-speed linear array APD FMCW LIDAR experimental platform. The results show that the VRCPSD algorithm has a better spectrum correction effect on the LIDAR experimental platform. This algorithm can reduce the margin of error to the centimeter level. Therefore, the algorithm is promising in that it can improve the signal waveform of the FMCW laser radar ranging system, make the spectrum get better correction and make the distance more accurate.

Parametric Decomposition of Pulsed Lidar Signals with Noise Corruption Using FRFT Spectrum Analysis

The parametric decomposition of full-waveform Lidar data is challenging when faced with heavy noise scenarios. In this paper, we report a fractional Fourier transform (FRFT)-based approach for accurate parametric decomposition of pulsed Lidar signals with noise corruption. In comparison with other joint time-frequency analysis (JTFA) techniques, FRFT is found to present a one-dimensional Lidar signal by a particular two-dimensional spectrum, which can exhibit the mathematical distribution of the multiple components in Lidar signals even with a heavy noise interference. A FRFT spectrum-processing solution with histogram clustering and moving LSM fitting is designed to extract the amplitude, time offset, and pulse width contained in the mathematical distribution. Extensive experimental results demonstrate that the proposed FRFT spectrum analysis method can remarkably outperform the conventional Levenberg–Marquardt-based method. In particular, it can accurately decompose the amplitudes, time offsets, and pulse widths of the pulsed Lidar signal with a −10-dB signal-to-noise-ratio by mean deviation ratios of 4.885%, 0.531%, and 7.802%, respectively.

Low walk error multi-stage cascade comparator for TOF LiDAR application

Aiming at the application of pulsed TOF LiDAR, this paper propose a low walk error multi-stage comparator based on the double threshold method. In order to achieve high-speed comparison output, the LVDS interface is used to output the data of the comparator. The dual-channel comparator is implemented using the SMIC 0.18 μm process which achieves a propagation delay of 620 ps and an input bandwidth of 256 MHz. Thanks to the multi-stage design, the walk error of the comparator is only 196 ps. It supports the minimum pulse width of 931 ps, the rms random jitter of 1.90 ps, and the power consumption of 39.6 mW.

Retrieval algorithm for the column CO<sub>2</sub> mixing ratio from pulsed multi-wavelength lidar measurements

Abstract. The retrieval algorithm for CO2 column mixing ratio from measurements of a pulsed multi-wavelength integrated path differential absorption (IPDA) lidar is described. The lidar samples the shape of the 1572.33 nm CO2 absorption line at multiple wavelengths. The algorithm uses a least-squares fit between the CO2 line shape computed from a layered atmosphere model and that sampled by the lidar. In addition to the column-average CO2 dry-air mole fraction (XCO2), several other parameters are also solved simultaneously from the fit. These include the Doppler shift at the received laser signal wavelength, the product of the surface reflectivity and atmospheric transmission, and a linear trend in the lidar receiver's spectral response. The algorithm can also be used to solve for the average water vapor mixing ratio, which produces a secondary absorption in the wings of the CO2 absorption line under humid conditions. The least-squares fit is linearized about the expected XCO2 value, which allows the use of a standard linear least-squares fitting method and software tools. The standard deviation of the retrieved XCO2 is obtained from the covariance matrix of the fit. The averaging kernel is also provided similarly to that used for passive trace-gas column measurements. Examples are presented of using the algorithm to retrieve XCO2 from measurements of the NASA Goddard airborne CO2 Sounder lidar that were made at constant altitude and during spiral-down profile maneuvers.

Micro Pulse Lidar measurements in coincidence with CALIPSO overpasses: Comparison of tropospheric aerosols over Kattankulathur (12.82oN, 80.04oE)

In this paper, we present validation of the cloud aerosol lidar with orthogonal polarization (CALIOP) level 1 and level 2 tropospheric aerosols products in coincidence to Micro Pulse Lidar (MPL) observations under different sky conditions and different seasons during March 2016–December 2018 over a tropical coastal station Kattankulathur (12.83oN, 80.04oE). In total, 33 simultaneous profiles during clear-sky (18 cases) and cloudy (15 cases; 7 mid-tropospheric (MT) clouds and 8 cirrus clouds cases) conditions are observed, out of which 5, 13, 6, and 9 cases are during winter, pre-monsoon, southwest (SW) monsoon and northeast (NE) monsoon seasons, respectively. CALIOP underestimates MPL within the boundary layer and overestimates in the free troposphere during both the clear-sky and cirrus conditions. In the clear-sky conditions, the mean bias of the level 1 aerosol products is found to be −14 ± 29% (18 ± 19%) below 3.0 km (over 3–10 km) while it is −39 ± 26% (33 ± 24%) below 3.0 km (over 3–8 km) underlying the cirrus clouds. The comparison underlying the thick MT clouds is not reliable. However, a better comparison is observed in the cases of thin MT clouds. A strong seasonal variation in the vertical distribution of the aerosol loadings near the surface with maximum (minimum) loading ~0.01 ± 0.005 km−1sr−1 (~0.004 ± 0.002 km−1sr−1) is observed during the winter (SW monsoon) season. The mean bias of level 2 aerosol profiles over the altitude 0.3–5 km is found to be 14 ± 28%, 15 ± 44%, −14 ± 25%, and 24 ± 34% during the winter, pre-monsoon, SW monsoon, and NE monsoon seasons, respectively.

Portable Pulsed Coherent Lidar for Noncooperation Targets at the Few-Photon Level.

The decoherence in coherent lidar becomes serious with the increase in distance. A small laser spot can suppress the decoherence of the echo light from noncooperation targets. However, it is very difficult to keep a small light spot over a long distance. In this paper, a pulsed coherent lidar with high sensitivity at the few-photon level was demonstrated. A phase plate was used to modulate the wavefront of the laser to achieve 100 m focusing which reduced the decoherence effect. Based on coherent detection and time-of-flight (TOF) measurements, long-distance laser ranging and imaging on all days was realized. A signal classification and superposition method was used to extract the echo signal submerged in noise. The system was experimentally demonstrated by ranging different noncooperation targets within 105.0 m. The measurement rate was 10 k/s, and the measurement uncertainty was 1.48 cm. In addition, laser imaging was realized at ~50.0 m. The system was simple and portable as well as eye safe, and it may offer new application possibilities in automated vehicle lidar.

Airborne Testing of 2-μm Pulsed IPDA Lidar for Active Remote Sensing of Atmospheric Carbon Dioxide

The capability of an airborne 2-μm integrated path differential absorption (IPDA) lidar for high-accuracy and high-precision active remote sensing of weighted-average column dry-air volume mixing ratio of atmospheric carbon dioxide (XCO2) is demonstrated. A test flight was conducted over the costal oceanic region of the USA to assess instrument performance during severe weather. The IPDA targets CO2 R30 absorption line using high-energy 2-μm laser transmitter. HgCdTe avalanche photodiode detection system is used in the receiver. Updated instrument model included range correction factor to account for platform attitude. Error budget for XCO2 retrieval predicts lower random error for longer sensing column length. Systematic error is dominated by water vapor (H2O) through dry-air number density derivation, followed by H2O interference and ranging related uncertainties. IPDA XCO2 retrieval results in 404.43 ± 1.23 ppm, as compared to 405.49 ± 0.01 ppm from prediction models, using consistent reflectivity and steady elevation oceanic surface target. This translates to 0.26% and 0.30% relative accuracy and precision, respectively. During gradual spiral descend, IPDA results in 404.89 ± 1.19 ppm as compared model of 404.75 ± 0.73 ppm indicating 0.04% and 0.23% relative accuracy, respectively. Challenging cloud targets limited retrieval accuracy and precision to 2.56% and 4.78%, respectively, due to H2O and ranging errors.

LiSBOA (LiDAR Statistical Barnes Objective Analysis) for optimal design of lidar scans and retrieval of wind statistics – Part 1: Theoretical framework

Abstract. A LiDAR Statistical Barnes Objective Analysis (LiSBOA) for the optimal design of lidar scans and retrieval of the velocity statistical moments is proposed. LiSBOA represents an adaptation of the classical Barnes scheme for the statistical analysis of unstructured experimental data in N-dimensional space, and it is a suitable technique for the evaluation over a structured Cartesian grid of the statistics of scalar fields sampled through scanning lidars. LiSBOA is validated and characterized via a Monte Carlo approach applied to a synthetic velocity field. This revisited theoretical framework for the Barnes objective analysis enables the formulation of guidelines for the optimal design of lidar experiments and efficient application of LiSBOA for the postprocessing of lidar measurements. The optimal design of lidar scans is formulated as a two-cost-function optimization problem, including the minimization of the percentage of the measurement volume not sampled with adequate spatial resolution and the minimization of the error on the mean of the velocity field. The optimal design of the lidar scans also guides the selection of the smoothing parameter and the total number of iterations to use for the Barnes scheme. LiSBOA is assessed against a numerical data set generated using the virtual lidar technique applied to the data obtained from a large eddy simulation (LES). The optimal sampling parameters for a scanning Doppler pulsed wind lidar are retrieved through LiSBOA, and then the estimated statistics are compared with those of the original LES data set, showing a maximum error of about 4 % for both mean velocity and turbulence intensity.

Spectral correction of turbulent energy damping on wind lidar measurements due to spatial averaging

Abstract. Continuous advancements in pulsed wind lidar technology have enabled compelling wind turbulence measurements within the atmospheric boundary layer with probe lengths shorter than 20 m and sampling frequency on the order of 10 Hz. However, estimates of the radial velocity from the back-scattered lidar signal are inevitably affected by an averaging process within each probe volume, generally modeled as a convolution between the true velocity projected along the lidar line-of-sight and an unknown weighting function representing the energy distribution of the laser pulse along the probe length. As a result, the spectral energy of the turbulent velocity fluctuations is damped within the inertial subrange, thus not allowing one to take advantage of the achieved spatio-temporal resolution of the lidar technology. We propose to correct the turbulent energy damping on the lidar measurements by reversing the effect of a low-pass filter, which can be estimated directly from the power spectral density of the along-beam velocity component. Lidar data acquired from three different field campaigns are analyzed to describe the proposed technique, investigate the variability of the filter parameters and, for one dataset, assess the corrected velocity variance against sonic anemometer data. It is found that the order of the low-pass filter used for modeling the energy damping on the lidar velocity measurements has negligible effects on the correction of the second-order statistics of the wind velocity. In contrast, the cutoff wavenumber plays a significant role in spectral correction encompassing the smoothing effects connected with the lidar probe length. Furthermore, the variability of the spatial averaging on wind lidar measurements is investigated for different wind speed, turbulence intensity, and sampling height. The results confirm that the effects of spatial averaging are enhanced with decreasing wind speed, smaller integral length scale and, thus, for smaller sampling height. The method proposed for the correction of the second-order turbulent statistics of wind-velocity lidar data is a compelling alternative to existing methods because it does not require any input related to the technical specifications of the used lidar system, such as the energy distribution over the laser pulse and lidar probe length. On the other hand, the proposed method assumes that surface-layer similarity holds.

Measuring the Micro Deformation and Crack of Rock Surface and Make Robot Intelligent Walking Path from Pulse Lidar Profiler

Derived from accumulated lidar point cloud, 3D model building appears to be a crucial technology for autonomous navigation of car. In this paper, we present a method of monitoring rock wall cracks and micro rock top displacement of underground tunnel by using pulse lidar profiler, so as to achieve the purpose of timely and real-time early warning. With the help of the Internet of things, cloud data and fog computing, the pulse lidar profiler is regarded as an extended terminal of cloud computing. It performs many tasks such as daily contour data and key electronic equipment monitoring status data recording, danger alarm calculation and emergency situation uploading to the cloud database.

Dynamic Path Planning of Underwater Vehicle Based on Pulse Lidar Profiler

In the underwater environment, the speed of light is much faster than that of sonar, so it can be used to sample and detect more intensively in space and high frequency in time. A better strategy is to integrate sonar and lidar into an integrated device. In military affairs, lidar sonar system is used for identification of underwater artificial works and fixed-point blasting. In the civil field, aquaculture, scientific research and sampling, and underwater infrastructure exploration are the main areas. This paper analyzes the application of pulse lidar profiler system integrated with multiple detection methods in the dynamic path planning of underwater vehicle. Three colors of “red, orange, red sauce” were used as the warm color light source group, and three colors of “blue, green, purple” were used as the cold color light source group. Through matrix operation, underwater objects with almost all colors can be quickly reached and superimposed. The speed of sound wave is slow, but the bypass performance is very good, which fully supplements the blind area of light source.

Application of Semantic Analysis System in Intelligent Navigation Path Planning Based on Pulse Lidar Profiler

The daily operation and maintenance of rock tunnel and coal mine roadway focuses on ensuring safety and data validity. Although a lot of related research has been published, most of them focus on one or several categories of dangerous situation handling. This research combines the concepts of pulse lidar profiler and semantic analysis system, and proposes a new system oriented security operation and maintenance method. The scanning of the conventional area can even be skipped in the case of time constraint, but the sub key area and the primary key area must be scanned and monitored strictly according to the scanning times converted from the weight value of real-time calibration. For the primary focus area, the maximum scanning cycle of 7 cycles can be specified directly. In short, it classifies the continuous spatial point cloud data scanned by pulse lidar profiler through semantic analysis system, and allocates weights according to different classes of object mapping, and makes multiple scanning decision arrangement for high weight classes.

Distance–Intensity Image Strategy for Pulsed LiDAR Based on the Double-Scale Intensity-Weighted Centroid Algorithm

We report on a self-adaptive waveform centroid algorithm that combines the selection of double-scale data and the intensity-weighted (DSIW) method for accurate LiDAR distance–intensity imaging. A time window is set to adaptively select the effective data. At the same time, the intensity-weighted method can reduce the influence of sharp noise on the calculation. The horizontal and vertical coordinates of the centroid point obtained by the proposed algorithm are utilized to record the distance and echo intensity information, respectively. The proposed algorithm was experimentally tested, achieving an average ranging error of less than 0.3 ns under the various noise conditions in the listed tests, thus exerting better precision compared to the digital constant fraction discriminator (DCFD) algorithm, peak (PK) algorithm, Gauss fitting (GF) algorithm, and traditional waveform centroid (TC) algorithm. Furthermore, the proposed algorithm is fairly robust, with remarkably successful ranging rates of above 97% in all tests in this paper. Furthermore, the laser echo intensity measured by the proposed algorithm was proved to be robust to noise and to work in accordance with the transmission characteristics of LiDAR. Finally, we provide a distance–intensity point cloud image calibrated by our algorithm. The empirical findings in this study provide a new understanding of using LiDAR to draw multi-dimensional point cloud images.

EMD and VMD-GWO parallel optimization algorithm to overcome Lidar ranging limitations.

Pulsed Lidar can obtain rich target information in one pulse, but the echo pulse signal is extremely susceptible to low laser transmitting power and complex target environments, resulting in an amplitude that is too low, which affects detection efficiency and ranging accuracy. In this paper, a variational modal decomposition based on gray wolf optimizer (VMD-GWO) and an empirical mode decomposition (EMD) parallel for denoising and signal enhancement in pulse Lidar is proposed and demonstrated completely. First, the adaptive strategy EMD is used for denoising the signal to obtain effective information. The combination of optimal VMD parameters of quadratic penalty αv and decomposition mode k was obtained by using the GWO to select the modal component with the smallest center frequency as effective information. Second, EMD and VMD-GWO parallel optimization algorithms are used to reconstruct the signal to obtain denoising and enhanced signals. Finally, a real experiment was carried out with the pulse Lidar ranging equipment. Our method compared with EMD-soft, EMD-VMD,WL-db4//EMD-DT and WL-db4//VMD has achieved greater improvement. When the target distance and the reflectivity of the reflectivity plate are 30 m and 10%, respectively, the peak signal-to-noise ratio (PSNR) of the weak echo signal calculated by our method can reach 11.5284 dB. And when in the dead zone of the system ranging, it is effectively denoising and enhancing the signal.

Pseudo-random modulation continuous-wave lidar for the measurements of mesopause region sodium density.

The sodium fluorescence lidar utilizes a 589 nm narrowband pulse laser system to measure mesopause region atomic sodium density, atmospheric temperature, and wind. However, this system is complicated and unstable. The continuous-wave (CW) sodium laser system can achieve ultra-narrow bandwidth, all-solid-state, and small compact size, as such it is extremely valuable for mobile, aircraft, and space-borne applications. In this study, we developed the first pseudo-random modulated CW (PMCW) sodium lidar by using an electro-optic modulated narrowband 589 nm CW laser with an output power of ∼1.2W. A pseudorandom M-sequence-code with a length of 127 is used to achieve altitude information by modulating laser and then decoding photon signals. Also, a biaxial structure with 9 m separation between the optical axes of the transmitter and receiver is designed to suppress the strong near-ground signals, which are crucial for improving the signal-to-noise ratio (SNR) of the PMCW lidar system. Nighttime measurements on December 2-4, 2019 show that the SNR at sodium layer peak is more than 10, corresponding to a statistical uncertainty of less than 10% in sodium density with temporal and spatial resolutions of 5 min and 1.05 km respectively. The comparison of vertical profiles of sodium density simultaneously observed by PMCW lidar and collocated pulse lidar shows good agreement.

FPGA-based digital chaotic anti-interference lidar system.

We use the chaotic signal generated by a field-programmable gate array (FPGA) to establish a digital chaotic pulse lidar system, which can achieve mid-range detection and high ranging accuracy without a complex optical structure. We employ the FPGA to generate random sequences with different modulation rates based on different chaotic iterative equations and initial values. By selecting the initial value and improved logistic equations, we successfully achieve centimeter-level ranging accuracy. Experiments have proved that the digital chaotic lidar system can effectively resist the interference of chaotic signals, square wave signals, and sine wave signals with modulation frequencies of 10 MHz, 100 MHz, 200 MHz, and 1 GHz, showing its strong anti-interference capability.

Determination of turbulence parameters from the spectra of vertical wind velocity component measured by a pulsed coherent Doppler lidar. Part III. Experiment on the coast of Lake Baikal

Determination of turbulence parameters from the spectra of vertical wind velocity component measured by a pulsed coherent Doppler lidar. Part III. Experiment on the coast of Lake Baikal