Lidar Performance Research Articles

Hierarchical Attention-Based Sensor Fusion Strategy for Depth Estimation in Diverse Weather

In this paper, we propose a hierarchical attention-based sensor fusion strategy for depth estimation under various weather conditions. Multiple-sensor fusion is proven as a promising solution for predicting accurate depth maps in diverse weather conditions, especially for extreme weather conditions. However, most of the current studies simply fuse the information from different sensors without jointly considering the difference in their performance at the sensor level and feature level. To fill this gap, our hierarchical attention-based fusion strategy uses two attention mask-generation modules that weigh sensor data from branches (i.e. different sensors) and features. With the cooperation of these two masks, our system is able to determine the adaptive contribution of each sensor as well as the individual contribution of each feature in the sensor regarding their performance in different weather. We compare the proposed methods with the baseline, i.e. the late fusion Sparse-to-Dense model, and two extended models individually with the branch-wise-only and feature-wise-only masks. The results show a robust and superior performance of our methods even in clear environments where the baseline already performs well enough. Moreover, we investigate the performance of RGB camera, radar, and LiDAR in foggy environments comprehensively by visualizing the generated mask. Our results show a significantly increased importance of radar sensors in extreme weather conditions, e.g. dense fog.

Simulation of Compact Spaceborne Lidar with High-Repetition-Rate Laser for Cloud and Aerosol Detection under Different Atmospheric Conditions

To provide references for the design of the lab’s upcoming prototype of the compact spaceborne lidar with a high-repetition-rate laser (CSLHRL), in this paper, the detection signal of spaceborne lidar was simulated by the measured signal of ground-based lidar, and then, the detection capability of spaceborne lidar under different atmospheric conditions was evaluated by means of the signal-to-noise ratio (SNR), volume depolarization ratio (VDR) and attenuated color ratio (ACR). Firstly, the Fernald method was used to invert the optical parameters of cloud and aerosol with the measured signal of ground-based lidar. Secondly, the effective signal of the spaceborne lidar was simulated according to the known atmospheric optical parameters and the parameters of the spaceborne lidar system. Finally, by changing the cumulative laser pulse number and atmospheric conditions, a simulation was carried out to further evaluate the detection performance of the spaceborne lidar, and some suggestions for the development of the system are given. The experimental results showed that the cloud layer and aerosol layer with an extinction coefficient above 0.3 km−1 could be easily obtained when the laser cumulative pulse number was 1000 and the vertical resolution was 15 m at night; the identification of moderate pollution aerosols and thick clouds could be easily identified in the daytime when the laser cumulative pulse number was 10,000 and the vertical resolution was 120 m.

Effects of a variable linewidth laser and variable linewidth shape laser on coherent FMCW LiDAR

To investigate the tolerance of laser linewidth, a stable and variable light source is essential. This study proposes a novel method for generating a variable linewidth and variable light source using a lithium niobite phase modulator, achieved through the application of white Gaussian noise and random walk noise with a limited wall. The proposed approach was thoroughly examined through equations, simulations, and experiments. Further, a practical application was demonstrated while investigating the effects of variable linewidth and shape on FMCW LiDAR performance. The results highlight the importance of optimizing the light source for LiDAR applications to ensure the maximum accuracy and resolution.

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.

Analysis of Internal Angle Error of UAV LiDAR Based on Rotating Mirror Scanning

UAV LiDAR is a powerful tool for rapidly acquiring ground-based 3D spatial information and has been used in various applications. In addition to the ranging mechanism, the scanning method is also an important factor, affecting the performance of UAV LiDAR, and the internal angle error of LiDAR will seriously affect its measurement accuracy. Starting from the rotary scanning model of a single-sided mirror, this paper presents a comparative study of the characteristics of 45° single-sided mirror scanning, polygon prism scanning, polygon tower mirror scanning, and wedge mirror scanning. The error sources of the quadrangular tower mirror scanning are analyzed in detail, including the angle deviation between the direction of emitted laser and the rotation axis (typical 0.13 ± 0.18° and 0.85° ± 0.26°), the angle deviation between the mirror’s reflection plane and the rotation axis, and the surface angle deviation between multiple surfaces (typical ± 0.06°). As a result, the measurement deviation caused by the internal angle error can be as high as decimeter to meter, which cannot be fully compensated by simply adjusting the installation angle between the UAV and the LiDAR. After the calibration of the internal angle error, the standard deviation of the elevation difference between the point cloud and the control point is only 0.024 m in the flight experiment at 300 m altitude.

Numerical simulation model of an optical filter using an optical vortex.

Vortex beam has the potential to significantly improve the performance of lidar (light detection and ranging) and optical communication applications in which low signal-to-noise ratio (SNR) limits the detection/transmission range. The vortex beam method allows for spatially separating the coherent light (laser signal) from the incoherent light (the background radiation and multiple-scattered light) of the received signal. This paper presents results of a simulation model in which the optical vortex acts as an optical filter. We present instrument parameters that describe the filtering effect, e.g., the form of the vortex phase modulation function, the topological charge of the vortex and the focal length of a virtual Fresnel lens that is used for optical filtering. Preliminary experimental results show that the background radiation within the spectral filter bandwidth can be suppressed by as much as 95%. At the same time, we retain 97% of the coherent laser signal. Our simulation model will be used in future design of lidar instruments and optical communication systems in which the optical vortex method is used for optical filtering of the detected signals.

Numerical Assessment of Horizontal Scanning LIDAR Performance Via Comparative Study Method

LIDAR performance is often evaluated after assembled prototypes are deployed for field tests. However, this approach is resource-intensive, which necessitates more cost-effective ways to detect flaws and improve LIDAR design. In this work, we present numerical assessment of horizontal scanning LIDAR performance via comparative study method. This assessment method could evaluate LIDAR performance without physically assembling the unit, hence save resources and time. We demonstrate this using a hypothetical atmospheric LIDAR. In our assessment, Python™ was used to develop simulation algorithm based on LIDAR equation, while Koschmieder visibility theory was used in atmosphere modeling. Daytime visibility and MODTRAN® solar spectral radiance data were also incorporated for analysis. We then evaluated LIDAR performance based on signal-to-noise and range-corrected signal profiles. Lastly, we conducted comparative study of this hypothetical LIDAR setup with Shiina (light emitting diode) LIDAR and VAST (ground-based) LIDAR for horizontal distance of 1 km. Numerical analysis showed that hypothetical LIDAR could operate up to 1 km at night. During daytime, detection was limited to 94 m and 220 m for 532 nm and 808 nm channels respectively. Comparative study demonstrated that the hypothetical LIDAR excelled in nighttime detection range with acceptable daytime performance. Overall, the hypothetical LIDAR has met case study requirements. We demonstrate the feasibility of this numerical assessment via comparative study method by identifying possible improvements in laser module without experimental data verification.

3-D Multi-Input Multi-Output (MIMO) Pulsed Chaos Lidar Based on Time-Division Multiplexing

In this study, we propose and evaluate a 3D multi-input multi-output (MIMO) pulsed chaos lidar based on time-division multiplexing. By time-gating a chaos waveform sequentially at different times, chaos-modulated pulses for different channels that are uncorrelated with each other can be generated. To quantitatively evaluate the anti-interference/jamming capability, we investigated the detection performance of the MIMO chaos lidar under different jamming strengths and overlapped ratios between the jamming and the signal pulses. The overall detection probabilities of the chaos lidar and a conventional time-digital-converter-based pulsed lidar under the influence of interference/jamming were compared and we found that the chaos lidar exhibits strong resistance to the interference/jamming. Employing the 3D MIMO chaos lidar developed, we demonstrate 3D imaging under the influence of interference/jamming. By simultaneously scanning 2 different channels with overlapped field-of-views (FOVs), 3D images with large-FOV/low-resolution and small-FOV/high-resolution were obtained at the same time.

Behavior and mechanisms of Doppler wind lidar error in varying stability regimes

Abstract. Wind lidars are widespread and important tools in atmospheric observations. An intrinsic part of lidar measurement error is due to atmospheric variability in the remote-sensing scan volume. This study describes and quantifies the distribution of measurement error due to turbulence in varying atmospheric stability. While the lidar error model is general, we demonstrate the approach using large ensembles of virtual WindCube V2 lidar performing a profiling Doppler-beam-swinging scan in quasi-stationary large-eddy simulations (LESs) of convective and stable boundary layers. Error trends vary with the stability regime, time averaging of results, and observation height. A systematic analysis of the observation error explains dominant mechanisms and supports the findings of the empirical results. Treating the error under a random variable framework allows for informed predictions about the effect of different configurations or conditions on lidar performance. Convective conditions are most prone to large errors (up to 1.5 m s−1 in 1 Hz wind speed in strong convection), driven by the large vertical velocity variances in convective conditions and the high elevation angle of the scanning beams (62∘). Range-gate weighting induces a negative bias into the horizontal wind speeds near the surface shear layer (−0.2 m s−1 in the stable test case). Errors in the horizontal wind speed and direction computed from the wind components are sensitive to the background wind speed but have negligible dependence on the relative orientation of the instrument. Especially during low winds and in the presence of large errors in the horizontal velocity estimates, the reported wind speed is subject to a systematic positive bias (up to 0.4 m s−1 in 1 Hz measurements in strong convection). Vector time-averaged measurements can improve the behavior of the error distributions (reducing the 10 min wind speed error standard deviation to <0.3 m s−1 and the bias to <0.1 m s−1 in strong convection) with a predictable effectiveness related to the number of decorrelated samples in the time window. Hybrid schemes weighting the 10 min scalar- and vector-averaged lidar measurements are shown to be effective at reducing the wind speed biases compared to cup measurements in most of the simulated conditions, with time averages longer than 10 min recommended for best use in some unstable conditions. The approach in decomposing the error mechanisms with the help of the LES flow field could be extended to more complex measurement scenarios and scans.

Simulated Lunar Surface Hydration Measurements Using Multispectral Lidar at 3µm.

Accurately measuring the variability of spectroscopic signatures of hydration (H2O + OH) on the illuminated lunar surface at 3 μm as a function of latitude, lunar time of day, and composition is crucial to determining the generation and destruction mechanisms of OH species and understanding the global water cycle. A prime complication in analysis of the spectroscopic feature is the accurate removal of thermal emission, which can modify or even eliminate the hydration feature depending on the data processing methods used and assumptions made. An orbital multispectral lidar, with laser illumination at key diagnostic wavelengths, would provide uniform, zero‐phase geometry, complete latitude and time of day coverage from a circular polar orbit, and is agnostic to the thermal state of the surface. We have performed measurement simulations of a four‐wavelength multispectral lidar using spectral mixtures of hydrated mid‐ocean‐ridge basalt (MORB) glasses and lunar regolith endmembers to assess the lidar performance in measuring hydration signatures on the lunar surface. Our results show a feasible system with wavelengths at 1.5 μm, 2.65 μm, 2.8 μm, and 3.1 μm can measure lunar hydration with a precision of 52 ppm (1σ) or better. These results, combined with the uniform measurement capabilities of multispectral lidar make it a valuable spectroscopic technique for elucidating mechanisms of OH/H2O generation, migration, and destruction.

Performance of GEDI Space-Borne LiDAR for Quantifying Structural Variation in the Temperate Forests of South-Eastern Australia

Monitoring forest structural properties is critical for a range of applications because structure is key to understanding and quantifying forest biophysical functioning, including stand dynamics, evapotranspiration, habitat, and recovery from disturbances. Monitoring of forest structural properties at desirable frequencies and cost globally is enabled by space-borne LiDAR missions such as the global ecosystem dynamics investigation (GEDI) mission. This study assessed the accuracy of GEDI estimates for canopy height, total plant area index (PAI), and vertical profile of plant area volume density (PAVD) and elevation over a gradient of canopy height and terrain slope, compared to estimates derived from airborne laser scanning (ALS) across two forest age-classes in the Central Highlands region of south-eastern Australia. ALS was used as a reference dataset for validation of GEDI (Version 2) dataset. Canopy height and total PAI analyses were carried out at the landscape level to understand the influence of beam-type, height of the canopy, and terrain slope. An assessment of GEDI’s terrain elevation accuracy was also carried out at the landscape level. The PAVD profile evaluation was carried out using footprints grouped into two forest age-classes, based on the areas of mountain ash (Eucalyptus regnans) forest burnt in the Central Highlands during the 1939 and 2009 wildfires. The results indicate that although GEDI is found to significantly under-estimate the total PAI and slightly over-estimate the canopy height, the GEDI estimates of canopy height and the vertical PAVD profile (above 25 m) show a good level of accuracy. Both beam-types had comparable accuracies, with increasing slope having a slightly detrimental effect on accuracy. The elevation accuracy of GEDI found the RMSE to be 10.58 m and bias to be 1.28 m, with an R2 of 1.00. The results showed GEDI is suitable for canopy densities and height in complex forests of south-eastern Australia.

Remote sensing of seawater optical properties and the subsurface phytoplankton layer in coastal waters using an airborne multiwavelength polarimetric ocean lidar.

The vertical profiles of the seawater optical properties and subsurface phytoplankton layer observed during an airborne lidar flight experiment carried out on 29 January 2021 in the coastal waters near Qionghai city were studied. We employed a hybrid inversion model combining the Klett and perturbation retrieval methods to estimate the seawater optical properties, while the vertical subsurface phytoplankton layer profiles were obtained by an adaptive evaluation. The airborne lidar data preprocessing scheme and inversion of the seawater optical properties were described in detail, and the effects of water environment parameters on the airborne lidar detection performance in coastal waters were discussed. The obtained seawater optical properties and phytoplankton layer profiles exhibit characteristic spatiotemporal distributions. The vertical stratification of seawater optical properties along a flight track from 19.19°N to 19.27°N is more pronounced than that from 19.27°N to 19.31°N. The subsurface phytoplankton layer appears along the flight track at water depths of 5-14 m with a thickness of 2-8.3 m. The high concentrations of chlorophyll, colored dissolved organic matter (CDOM), and suspended particulate matter (SPM) in coastal waters are the main factors leading to the shallower detection depth for airborne lidar. A 532 nm laser emission wavelength is more suitable than 486 nm for investigating coastal waters. The 532 nm receiving channel with 25 mrad receiving field of view achieves a better detection performance than that with 6 mrad. These results indicate that lidar technology has great potential for the wide-range and long-term monitoring of coastal waters.

Evaluation of Aeolus L2B wind product with wind profiling radar measurements and numerical weather prediction model equivalents over Australia

Abstract. Carrying a laser Doppler instrument, the Aeolus satellite was launched in 2018, becoming the first mission for atmospheric wind profile measurements from space. Before utilizing the Aeolus winds for different applications, evaluating their data quality is essential. With the help of ground-based wind profiling radar measurements and the European Centre for Medium-Range Weather Forecasts (ECMWF) model equivalents, this study quantifies the error characteristics of Aeolus L2B (baseline-11) near-real-time horizontal line-of-sight winds across Australia during October 2020–March 2021 by using both inter-comparison and triple collocation analysis. The results of the inter-comparison analysis indicate that both Rayleigh-clear winds and Mie-cloudy winds are in good agreement with the ground-based radar measurements with overall absolute mean biases smaller than 0.7 m s−1 and correlation coefficients larger than or equal to 0.9. Moreover, assuming the radar measurements as the reference data set, Mie-cloudy winds are shown to be more precise than Rayleigh-clear winds with an overall random error of 4.14 and 5.81 m s−1, respectively. Similar results were also found from triple collocation analysis, with error standard deviations of 5.61 and 3.50 m s−1 for Rayleigh-clear winds and Mie-cloudy winds. In addition, the Mie channel is shown to be more capable of capturing the wind in the planetary boundary layer (< 1500 m). The findings of this study demonstrate the good performance of space-borne Doppler lidar for wind profiling and provide valuable information for data assimilation in numerical weather prediction.

Performance Improvement for Single-Photon LiDAR with Dead Time Selection

Compared with the impulse LiDAR, the single-photon LiDAR has higher measurement sensitivity in the prominent feature, especially for space-based long-distance imaging. The distance measurement and the detection probability are the critical performance for LiDAR. The ranging of single-photon LiDAR is mainly different from the photon ranging of pulsed LiDAR. Dead time has a significant effect on distance measurement accuracy and detection probability, which are key parameters for detectors when implementing sound control. Therefore, the model of detector dead time, measurement accuracy, and detection probability should be established, and simulation results that meet application requirements should be achieved. Based on the single-photon ranging theory, the dead time, measurement accuracy, and detection probability model of single-photon LiDAR are studied. Furthermore, the systematic simulation of different contrasts is carried out according to the model. The simulation results demonstrate that the model can accurately perform the relationship between dead time and single-photon LiDAR system parameters. The research results can prove the design and verification of single-photon LiDAR dead time.

Performance Assessment of Mobile Laser Scanning Systems Using Velodyne Hdl-32e

Mapping systems using multi-beam LiDARs are widely used nowadays for different geospatial applications graduating from indoor projects to outdoor city-wide projects. These mobile mapping systems can be either ground-based or aerial-based systems and are mostly equipped with inertial navigation systems INS. The Velodyne HDL-32 LiDAR is a well-known 360° spinning multi-beam laser scanner that is widely used in outdoor and indoor mobile mapping systems. The performance of such LiDARs is an ongoing research topic which is quite important for the quality assurance and quality control topic. The performance of this LiDAR type is correlated to many factors either related to the device itself or the design of the mobile mapping system. Regarding design, most of the mapping systems are equipped with a single Velodyne HDL32 in a specific orientation angle which is different among the mapping systems manufacturers. The LiDAR orientation angle has a significant impact on the performance in terms of the density and coverage of the produced point clouds. Furthermore, during the lifetime of this multi-beam LiDAR, one or more beams may be defected and then either continue the production or returned to the manufacturer to be fixed which then cost time and money. In this paper, the design impact analysis of a mobile laser scanning (MLS) system equipped with a single Velodyne HDL-32E will be clarified and a clear relationship is given between the orientation angle of the LiDAR and the output density of points. The ideal angular orientation of a single Velodyne HDL-32E is found to be at 35° in a mobile mapping system. Furthermore, we investigated the degradation of points density when one of the 32 beams is defected and quantified the density loss percentage and to the best of our knowledge, this is not presented in literature before. It is found that a maximum of about 8% point density loss occurs on the ground and 4% on the facades when having a defected beam of the Velodyne HDL-32E.

Simulation and optimization of Fe resonance fluorescence lidar performance for temperature-wind measurement.

Fe resonance fluorescence lidar (Fe lidar) is considered an ideal candidate for temperature and wind measurement in the mesosphere and lower thermosphere region. However, considering the complexity of it, only a few Fe lidars have been operated in a few locations. To develop a Fe lidar with high performance, simulation work is the first important step. A simulation model is built in this paper. The expressions for the temperature-wind uncertainties are derived using the error propagation method. Within the limit of saturation effect, an index decomposition of the lidar and atmospheric parameters are performed. When the dwell time and central frequency shift are optimized to 0.205 and 932 MHz at night and 0.212 and 687 MHz during the day, night and daytime calibration curves are acquired, and after confirming the simulation parameters, the performance of Fe lidar is also evaluated. The simulation model could provide a valuable guidance for Fe lidar design.

A LiDAR–Camera Fusion 3D Object Detection Algorithm

3D object detection with LiDAR and camera fusion has always been a challenge for autonomous driving. This work proposes a deep neural network (namely FuDNN) for LiDAR–camera fusion 3D object detection. Firstly, a 2D backbone is designed to extract features from camera images. Secondly, an attention-based fusion sub-network is designed to fuse the features extracted by the 2D backbone and the features extracted from 3D LiDAR point clouds by PointNet++. Besides, the FuDNN, which uses the RPN and the refinement work of PointRCNN to obtain 3D box predictions, was tested on the public KITTI dataset. Experiments on the KITTI validation set show that the proposed FuDNN achieves AP values of 92.48, 82.90, and 80.51 at easy, moderate, and hard difficulty levels for car detection. The proposed FuDNN improves the performance of LiDAR–camera fusion 3D object detection in the car category of the public KITTI dataset.

Modelling the spectral shape of continuous-wave lidar measurements in a turbulent wind tunnel

Abstract. This paper describes the development of a theoretical model for the turbulence spectrum measured by a short-range, continuous-wave lidar (light detection and ranging). The lidar performance was assessed by measurements conducted with two WindScanners in an open-jet wind tunnel equipped with an active grid, for a range of different turbulent wind conditions. A hot-wire anemometer is used as reference to assess the lidar's measured statistics, time series and spectra. In addition to evaluating the statistics, the correlation between the time series and the root-mean-square error (RMSE) on the wind speed, the turbulence spectrum measured by the lidar is compared with a modelled spectrum. The theoretical spectral model is applied in the frequency domain, using a Lorentzian filter in combination with Taylor's frozen turbulence hypothesis for the probe length averaging effect and an added white noise term, evaluated by qualitatively matching the lidar measurement spectrum. High goodness-of-fit coefficients and low RMSE values between the hot wire and WindScanner were observed for the measured time series. The correlation showed an inverse relationship with the prevalent turbulence intensity in the flow for cases with a comparable power spectrum shape. Larger flow structures can be captured more accurately by the lidar, whereas small-scale turbulent flow structures are partly filtered out as a result of the lidar's probe volume averaging effect. It is demonstrated that an accurate way to define the cut-off frequency at which the lidar's power spectrum starts to deviate from the hot-wire reference spectrum is the frequency at which the coherence drops below 0.5. This coherence-based cut-off frequency increases linearly with the mean wind speed and is generally an order of magnitude lower than the probe length equivalent cut-off frequency, estimated according to a simple model based on the full width at half maximum (FWHM) of the laser beam intensity along the line of sight and assuming Taylor's frozen turbulence hypothesis. A convincing match between the modelled and the measured WindScanner power spectrum was found for various different cases, which confirmed that the deviation of the lidar's measured power spectrum in the higher frequency range can be analytically explained and modelled as a combination of a Lorentzian-shaped intensity function and white noise in the lidar measurement. Although the models were developed on the basis of wind tunnel measurements, they should be applicable to atmospheric boundary layer field measurements as well.

Numerical Simulation of Performance Improvement of Underwater Lidar by Using a Spiral Phase Plate as Spatial Filter

In turbid water, target reflected lidar signal is easily buried in “clutter” due to scattering. We proposed an underwater laser ranging model applying an optical vortex in the receiver to separate the scattering clutter from the target reflected signal. A spiral phase plate (SPP) was placed in front of the detector to convert the target reflected Gaussian beam to an optical vortex. While the scattering clutters were not able to be converted due to the loss of spatial coherence. Therefore, the target reflected signal and scattering clutters were spatially separated by the SPP. An underwater laser detection simulation using Zemax software was carried out. The numerical simulation showed that when the SPP was placed in front of the receiver, the contrast of signal to clutter of the detection was improved by blocking the scattering clutters which had a Gaussian distribution at the center on the detection plane. The effects of beam divergence and orbital angular momentum (OAM) order to the lidar performance were also analyzed.

Simulation analysis of a lidar performance for atmospheric temperature profile measurements based on the Fizeau interferometer and multichannel photomultiplier tube

AbstractIn this study, a lidar system based on the Fizeau interferometer and photomultiplier tube array is designed to analyze the entire Rayleigh‐Brillouin spectrum aiming at obtaining the atmospheric temperature profiles. The laser wavelength emitted by the lidar is 355 nm with the pulse energy of 20 mJ, and the diameter of the receiving telescope is 0.6 m. We analyze the influence of the cumulative average of different pulse numbers on the accuracy of temperature inversion. The temperature inversion results in different height ranges are calculated and the results show that if the integration time is 100 s, the temperature deviation is less than 3 K in the altitude range below 24 km.