Lidar Detection Research Articles

Review of Photodetectors for Space Lidars

Photodetectors play a critical role in space lidars designed for scientific investigations from orbit around planetary bodies. The detectors must be highly sensitive due to the long range of measurements and tight constraints on the size, weight, and power of the instrument. The detectors must also be space radiation tolerant over multi-year mission lifetimes with no significant performance degradation. Early space lidars used diode-pumped Nd:YAG lasers with a single beam for range and atmospheric backscattering measurements at 1064 nm or its frequency harmonics. The photodetectors used were single-element photomultiplier tubes and infrared performance-enhanced silicon avalanche photodiodes. Space lidars have advanced to multiple beams for surface topographic mapping and active infrared spectroscopic measurements of atmospheric species and surface composition, which demand increased performance and new capabilities for lidar detectors. Higher sensitivity detectors are required so that multi-beam and multi-wavelength measurements can be performed without increasing the laser and instrument power. Pixelated photodetectors are needed so that a single detector assembly can be used for simultaneous multi-channel measurements. Photon-counting photodetectors are needed for active spectroscopy measurements from short-wave infrared to mid-wave infrared. HgCdTe avalanche photodiode arrays have emerged recently as a promising technology to fill these needs. This paper gives a review of the photodetectors used in past and present lidars and the development and outlook of HgCdTe APD arrays for future space lidars.

Switchable Dual-Wavelength Fiber Laser with Narrow-Linewidth Output Based on Parity-Time Symmetry System and the Cascaded FBG

In this paper, a dual-wavelength narrow-linewidth fiber laser based on parity-time (PT) symmetry theory is proposed and experimentally demonstrated. The PT-symmetric filter system consists of two optical couplers (OCs), four polarization controllers (PCs), a polarization beam splitter (PBS), and cascaded fiber Bragg gratings (FBGs), enabling stable switchable dual-wavelength output and single longitudinal-mode (SLM) operation. The realization of single-frequency oscillation requires precise tuning of the PCs to match gain, loss, and coupling coefficients to ensure that the PT-broken phase occurs. During single-wavelength operation at 1548.71 nm (λ1) over a 60-min period, power and wavelength fluctuations were observed to be 0.94 dB and 0.01 nm, respectively, while for the other wavelength at 1550.91 nm (λ2), fluctuations were measured at 0.76 dB and 0.01 nm. The linewidths of each wavelength were 1.01 kHz and 0.89 kHz, with a relative intensity noise (RIN) lower than −117 dB/Hz. Under dual-wavelength operation, the maximum wavelength fluctuations for λ1 and λ2 were 0.03 nm and 0.01 nm, respectively, with maximum power fluctuations of 3.23 dB and 2.38 dB. The SLM laser source is suitable for applications in long-distance fiber-optic sensing and coherent LiDAR detection.

Comparative Analysis and Optimal Selection of Calibration Functions in Pure Rotational Raman Lidar Technique

The pure rotational Raman (PRR) lidar technique relies on calibration functions (CFs) to extract temperature information from raw detection data. The choice of CF significantly impacts the accuracy of the retrieved temperature. In this study, we propose a method that combines multiple Monte Carlo simulation experiments with a statistical analysis, and we first conduct simulated comparisons of the calibration effects of different CFs while considering the impact of noise. We categorized ten common CFs into four groups based on their functional form and the number of calibration coefficients. Based on functional form, specifically, we defined 1/T = f(lnQ) as a forward calibration function (FCF) and lnQ = g(1/T) as a backward calibration function (BCF). Here, T denotes temperature, and Q denotes the signal intensity ratio. Their performance within and outside the calibration interval is compared across different integration times, smoothing methods, and reference temperature ranges. The results indicate that CFs of the same category exhibit similar calibration effects, while those of different categories exhibit notable differences. Within the calibration interval, the FCF performs better, especially with more coefficients. However, outside the calibration interval, the linear calibration function (which can be considered a two-coefficient FCF) has an obvious advantage. Conclusions based on the simulation results are validated with actual data, and the factors influencing calibration errors are discussed. Utilizing these findings to guide CF selection can enhance the accuracy and stability of PRR lidar detection.

Brillouin laser pumped tunable low-threshold mid-IR Kerr comb at 2 μm

Optical frequency combs in the 2 μm wavelength region are important for applications ranging from sensing of gases such as CO2 and CO to optical communications, LIDAR, and gravitational wave detection. The development of low-loss waveguides and high-Q microresonators with anomalous dispersion and the availability of tunable narrow linewidth lasers around 1.55 μm have enabled the realization of small footprint soliton combs and low-threshold Kerr combs in this wavelength region; demonstrations of microresonator frequency combs in the 2 μm wavelength region have been limited. Here, we harness an intracavity pumping scheme to demonstrate a low-threshold (<100 mW) microresonator Kerr comb at 2 μm. We exploit Brillouin lasing in a silica microsphere (∼310 μm diameter) to create an intracavity pump, which then generates a ∼140 nm wide Kerr comb in the backscattered Stokes direction. We demonstrate the tolerance of the comb generation scheme to microsphere dimensions and the input pump wavelength by achieving Kerr comb generation in microspheres of diameters ranging from 295 to 318 μm and also at different input pump wavelengths for a particular microsphere diameter. Intracavity pumping opens up opportunities for the development of soliton combs and Kerr combs in the mid-IR wavelength region for applications such as dual-comb spectroscopy, LIDAR, and optical communications.

A Three‐Frequency Ca+ Doppler Lidar for Ion Temperature Measurements in the E and F Regions

AbstractThe ion temperature is an important parameter for ionospheric detection, yet there is limited research on ion temperatures at altitude range from 80 to 300 km. Currently, a single‐frequency Ca+ ion optical parametric oscillator (OPO) Lidar system can be used to obtain the Ca+ ion density in this region at Yanqing Station, Beijing (40.4°N, 116.0°E). In this study, the ion temperature can be obtained by extending our original lidar to include three‐frequency Ca+ Doppler detection. This development represents a pioneering step on measuring ion temperatures by lidar in the ionospheric E‐F region. Preliminary results in the E region show that lidar temperatures at 90–105 km under the condition of smooth changes in Ca+ ion morphology align reasonably with satellite‐based observations and model‐derived temperatures. Additionally, the exploratory ion temperatures of the F layer peak heights at 200–300 km were obtained. Furthermore, parameter optimization and temperature error analysis in the E‐F region are explored, providing valuable insights for the development of Ca+ Doppler lidar systems. The advent of Ca+ Doppler lidar has greatly expanded the lidar detection altitude range of temperature and the possibilities for in‐depth research on ion temperature and velocity in regions affected by complex electrodynamic effects. These findings lay the foundation for subsequent studies of coupling processes in the ionospheric E‐F region.

Combination of LiDAR Detection and Green Integral Method for Calculating Irregular Cross-Section Geometric Properties of Deteriorated Components in Timber Historic Buildings

Timber components in historic buildings are susceptible to deterioration due to the complex external environment. The loss of material in these components and changes in their cross-section geometry significantly impact the stability and load-bearing capacity of historic buildings. A portable LiDAR device is utilized to acquire the cross-section geometry of the deteriorated components. The irregular cross-section profiles are extracted using point cloud slicing and the Alpha-Shape algorithm. Geometric characteristics such as cross-section area, moment of inertia, and moment of resistance are calculated using Green's integral method. The performance of this method is evaluated by measuring eight groups of deteriorated components with different cross-section characteristics and comparing it with five traditional methods.The results demonstrate that the proposed method improves the calculation accuracy by 1% to 21% relative to traditional methods, thereby enhancing reliability by 9% to 54%. Additionally, it reduces manual calculation workload and human error, while promoting calculation efficiency. The method exhibits excellent applicability and high efficiency, with an error below 3% when compared to the true value. This method proves valuable in evaluating the extent of deterioration in historic timber components and provides essential data for preventive conservation and restoration of historic timber buildings.

Multifunctional Radiation Conditioning Emitter for Laser and Infrared with Adaptive Radiative Cooling.

With the development of technology, multifunctional multiband emitters have been paid much attention due to their wide range of applications, such as LIDAR detection, spectroscopic sensing, and infrared thermal management. However, the development of such emitters is impeded by incompatible structural requirements of different electromagnetic wavebands. Here, we demonstrate coupled modulation between near-infrared (NIR) laser-wavelength and long-wavelength-infrared by constructing a multifunctional emitter (MFE) with a structure of Al/HfO2/VO2, utilizing the phase transition of VO2. The MFE displays excellent thermal modulation capability within the 8-14 μm range, achieving a thermal insulation effect (ε8-14μm = 0.18) at low temperatures, and heat dissipation effect (ε8-14μm = 0.64) at high temperatures. The MFE's radiation power regulation capability is 145.06 W m-2 between a temperature of 0 to 60 °C. Moreover, the MFE possesses a large reflectivity modulation value of 0.78 at NIR laser-wavelength (1.06 μm) with a short phase transition time of 1003 ms under 3 W cm-2 laser irradiation. This study provides a guideline for the coordinated control of electromagnetic waves and intelligent collaborative thermal management through simple structural design, thus, having broad implications in energy saving and thermal information processing.

Research on integrated LiDAR and multi-parameter detection of atmospheric transmittance, turbulence, and wind

An integrated LiDAR system has been reported, which can be used for simultaneous detection of atmospheric transmittance, turbulence, and wind along the same path. Through the integrated design of optics and mechanics, the size and weight of the system were effectively reduced. The comprehensive detection distance of atmospheric transmittance, atmospheric coherence length, and radial wind had also been achieved at least 4 kilometers. Comparative experiments have demonstrated that the detection results of the integrated LiDAR system and the near-surface meteorological observation system have standard deviations of less than 0.03 km−1 for extinction coefficient, 0.2 m/s for wind velocity, and 7.15 × 10−14 m−2/3 for C 2 n (atmospheric refractive index structure parameter), thus verifying the accuracy of the system detection. The reliability of the integrated LiDAR system was validated through six consecutive nights of continuous detection experiments, measuring three parameters simultaneously. Through analysis, the influence laws among atmospheric transmittance, coherence length, and wind were preliminarily explored. Significant variations in wind velocity can induce substantial fluctuations in atmospheric coherence length, and it is positively correlated with atmospheric transmittance. The integrated LiDAR system can provide a variety of reliable real-time detection data for further research on the laser transmission process in the atmosphere.

Terrestrial LiDAR derived 3D point cloud model, digital elevation model (DEM) and hillshade map for identification and evaluation of pavement distresses

The periodic assessment of pavement condition is one of the important requirements in ensuring not only the service life of the pavement but also for the safety of motorists as pavement distresses like potholes led to many fatal accidents in recent years in India. The traditional approach of manual evaluation is a cumbersome and time-consuming process which can be replaced by latest technologies like LiDAR. Literature on use of Terrestrial LiDAR for distress detection are very limited and even the reported studies have used mostly the raw point cloud data from LiDAR for detecting only selected distresses. However, there are many outputs which can be derived from Terrestrial LiDAR data like Digital Elevation Model (DEM), Hillshade, etc. which are not explored much. Hence in the present study, an attempt has been made to utilize all the possible outputs of Terrestrial LiDAR data, i.e., raw 3D model from point cloud data and LiDAR derived DEM and Hillshade to detect 15 pavement distresses in both bituminous and concrete pavement for a case study area of Vellore in Tamilnadu, India. Their suitability also was compared in order to find which output would be more suitable in identifying a particular distress on the road. The results revealed that Hillshade maps can detect all the pavement distresses except cracks when compared to 3D model and DEM. For the detection of pavement cracks, an image processing based solution using LiDAR data was tried out and was found to perform well in detecting the alligator cracks. The distress parameters such as length, width, depth, etc. were also calculated using LiDAR data and compared with the field observations. The error was found to be only few cms and thus indicate that the Terrestrial LiDAR can be employed to detect the pavement distresses accurately than the conventional manual methods.

Wavelength optimization of space-borne electro-optic dual-comb lidar for CO2 detection at 1572 nm

Wavelength optimization of space-borne electro-optic dual-comb lidar for CO2 detection at 1572 nm

Accuracy Evaluation of Differential Absorption Lidar for Ozone Detection and Intercomparisons with Other Instruments

Accuracy Evaluation of Differential Absorption Lidar for Ozone Detection and Intercomparisons with Other Instruments

Detection Performance Analysis of Marine Wind by Lidar and Radar under All-Weather Conditions

Accurate marine wind detection under all-weather conditions is crucial for maritime activities. The joint detection of lidar and radar is supposed to be a potential way to carry out the all-weather sensing of wind. However, their performance analysis has not been well studied, particularly in the far sea area, where the wind-tracing particles are quite different from those inland. Based on the particle distributions above the sea surface under different weather conditions, this study investigated the scattering and attenuation effects of lidar and radar waves in open sea areas with the Mie theory and T-matrix method. Then, the maximum detection range and velocity accuracies of lidar/radar were comprehensively analyzed based on detection principles to optimize the combination of lidar and radar. According to the simulation results, it was difficult to maintain the detection capability of a single lidar/radar under all-weather conditions, and 1.55 μm lidar and W-band radar presented a promising joint detection scheme, as they exhibited optimal weather adaptability in clear sky and precipitation conditions, respectively.

Simulation of atmospheric density detection by spaceborne Rayleigh lidar

Atmospheric density is one of the most important elements of the atmospheric environment. The accurate acquisition of atmospheric density in the near space plays a vital role in understanding atmospheric environment changes and aerospace operations. Spaceborne lidar, as an active observation method, has the advantages of high precision and all-time detection and is a unique payload for obtaining global atmospheric density. To promote the development of a spaceborne Rayleigh lidar payload, the key parameters of the payload need to be designed and optimized, and the detection performance needs to be simulated. In this paper, based on the atmospheric model, lidar equation, and load design parameters, the performance of spaceborne Rayleigh lidar for atmospheric density detection is simulated, and the atmospheric density of the global reference altitude obtained from ERA-5 reanalysis data to conduct simulation analysis of the atmospheric density of the global near space. The results show that the detection height ranges of night and day are 30–70 km and 30–40 km, respectively, and the detection accuracy is better than 10 %. Moreover, the distribution characteristics of the atmospheric density in the global near space with the change of altitude, season, latitude, and longitude are given. Finally, the feasibility of the proposed algorithm was verified by comparing it with the atmospheric density of TIMED/SABER and NRLMSIS-00 models. It provides a reference for the development of spaceborne Rayleigh lidar and global atmospheric density inversion.

Investigating long-term changes in polar stratospheric clouds above Antarctica during past decades: a temperature-based approach using spaceborne lidar detections

Investigating long-term changes in polar stratospheric clouds above Antarctica during past decades: a temperature-based approach using spaceborne lidar detections

A novel direct detection lidar compatible with software-defined radio

This paper proposes a novel direct detection lidar compatible with software-defined radio, which can effectively absorb the advantages of radio frequency technology. The radio frequency signal is firstly loaded onto the output light of the lidar through a fiber phase modulator and then demodulated from its backward reflected light through a combination of fiber Fabry-Perot interferometer and photodetector. The generation of the transmitting radio frequency signal and the sampling and processing of the receiving radio frequency signal are completed by a software-defined radio. Theoretically, it has been proven that the range and velocity of the target cause phase delay and Doppler frequency shift of the radio frequency signal loaded on the lidar, just like using the radio frequency signal to directly detect the target in radar. In the experiment, by programming the software-defined radio, the ranging and velocimetry algorithms of radar have been applied to this lidar. The theoretical and experimental results indicate that the lidar proposed in this paper has software definable characteristics. Through programming, different functions can be achieved, and in the future, more advanced algorithms of radar can be easily transplanted to further improve its performance.

Preliminary analysis of global column-averaged CO2 concentration data from the spaceborne aerosol and carbon dioxide detection lidar onboard AEMS

In contrast to the passive remote sensing of global CO2 column concentrations (XCO2), active remote sensing with a lidar enables continuous XCO2 measurements throughout the entire atmosphere in daytime and nighttime. The lidar could penetrate most cirrus and is almost unaffected by aerosols. Atmospheric environment monitoring satellite (AEMS, also named DQ-1) aerosol and carbon dioxide detection Lidar (ACDL) is a novel spaceborne lidar that implements a 1572 nm integrated path differential absorption (IPDA) method to measure the global XCO2 for the first time. In this study, special methods have been developed for ACDL data processing and XCO2 retrieval. The CO2 measurement data products of ACDL, including the differential absorption optical depth between the online and offline wavelengths, the integral weighting function, and XCO2, are presented. The results of XCO2 measurements over the period from 1st June 2022 to 30th June 2022 (first month data of ACDL) are analyzed to demonstrate the measurement capabilities of the spaceborne ACDL system.

Design of Lidar Receiving Optical System with Large FoV and High Concentration of Light to Resist Background Light Interference.

Lidar has the advantages of high accuracy, high resolution, and is not affected by sunlight. It has been widely used in many fields, such as autonomous driving, remote sensing detection, and intelligent robots. However, the current lidar detection system belongs to weak signal detection and generally uses avalanche photoelectric detector units as detectors. Limited by the current technology, the photosensitive surface is small, the receiving field of view is limited, and it is easy to cause false alarms due to background light. This paper proposes a method based on a combination of image-side telecentric lenses, microlens arrays, and interference filters. The small-area element detector achieves the high-concentration reception of echo beams in a large field of view while overcoming the interference of ambient background light. The image-side telecentric lens realizes that the center lines of the echo beams at different angles are parallel to the central axis, and the focus points converge on the same focal plane. The microlens array collimates the converged light beams one by one into parallel light beams. Finally, a high-quality aspherical focusing lens is used to focus the light on the small-area element detector to achieve high-concentration light reception over a large field of view. The system achieves a receiving field of view greater than 40° for a photosensitive surface detector with a diameter of 75 μm and is resistant to background light interference.

Automatic Miscalibration Detection and Correction of LiDAR and Camera Using Motion Cues

This paper aims to develop an automatic miscalibration detection and correction framework to maintain accurate calibration of LiDAR and camera for autonomous vehicle after the sensor drift. First, a monitoring algorithm that can continuously detect the miscalibration in each frame is designed, leveraging the rotational motion each individual sensor observes. Then, as sensor drift occurs, the projection constraints between visual feature points and LiDAR 3-D points are used to compute the scaled camera motion, which is further utilized to align the drifted LiDAR scan with the camera image. Finally, the proposed method is sufficiently compared with two representative approaches in the online experiments with varying levels of random drift, then the method is further extended to the offline calibration experiment and is demonstrated by a comparison with two existing benchmark methods.

DBN-GABP model for estimation of aircraft wake vortex parameters using Lidar data

Aircraft wake turbulence is an inherent outcome of aircraft flight, presenting a substantial challenge to air traffic control, aviation safety and operational efficiency. Building upon data obtained from coherent Doppler Lidar detection, and combining Dynamic Bayesian Networks(DBN) with Genetic Algorithm-optimized Backpropagation Neural Networks(GA-BPNN), this paper proposes a model for the inversion of wake vortex parameters. During the wake vortex flow field simulation analysis, the wind and turbulent environment were initially superimposed onto the simulated wake velocity field. Subsequently, Lidar-detected echoes of the velocity field are simulated to obtain a data set similar to the actual situation for model training. In the case study validation, real measured data underwent preprocessing and were then input into the established model. This allowed us to construct the wake vortex characteristic parameter inversion model. The final results demonstrated that our model achieved parameter inversion with only minor errors. In a practical example, our model in this paper significantly reduced the mean square error of the inverted velocity field when compared to the traditional algorithm. This study holds significant promise for real-time monitoring of wake vortices at airports, and is proved a crucial step in developing wake vortex interval standards.

Observation and study of consecutive dust storms in the Taklimakan desert from March 16 to 27, 2022, using reanalysis models and lidar

A series of severe dust storms hit the Taklimakan desert between March 16 and 27, 2022, significantly deteriorating air quality throughout China. This study presents a comprehensive analysis of the vertical structure of aerosols during these dust storms, as well as their causes and impacts on China's regional and city-scale air quality, utilizing data from reanalysis models, coherent Doppler wind lidar, and air quality monitoring stations. During dust storms, intense wind layers increase dust emissions, resulting in reduced lidar detection ranges and signal strengths. In addition, lower temperatures prevail due to sunlight absorption and scattering. Moreover, high-speed winds at high altitudes increase dust particles that serve as cloud condensation nuclei, leading to increased humidity, decreased temperature, and precipitation. The Taklimakan desert's trough serves as a wind convergence zone, which promotes favorable conditions for the initiation of dust storms. Due to the steep pressure gradients, strong winds enter the Taklimakan desert through the gap between its mountains in the east, coming from northern Xinjiang and Inner Mongolia via the Hexi corridor, which facilitates the lifting and transport of dust aerosols. Dust is transported long distances from the Taklimakan desert to the eastern coasts, impacting numerous cities along the way. The emissions from these dust storms swept across most Chinese provinces. Even though each dust storm was over in the Taklimakan desert, its effects on China's air quality continued for several days. The coarse PM concentrations (PM10–2.5) in Hotan, Kashgar, Aksu, Korla, Hami, Xining, Yinchuan, Taiyuan, and Beijing spiked to levels around 14, 36, 11, 6, 7, 12, 11, 12, and 6 times higher than their 2022 averages, respectively. This study provides valuable insights into the causes and effects of the Taklimakan desert dust storms, helping authorities develop effective mitigation plans.