Abstract:Reflective tomography lidar (RTL) reconstructs target contours by acquiring laser echo projection data, but incomplete angular detection in practice often leads to insufficient projection data. To address this issue, the authors proposes a target contour reconstruction method that combines the structural sparsity of projection data with a super-resolution convolutional neural network (SRCNN), based on the principles and technical implementation of RTL. This approach effectively resolves the failure of traditional algorithms when projection data suffers from severe angular deficiency. Different from conventional RTL imaging methods that directly incorporate sparse reconstruction models, the authors first recovers full-angle projection data by integrating sparse constraints with SRCNN based on geometry prior of the projection data, followed by standard RTL imaging algorithms to achieve complete targets contour reconstruction. To validate the effectiveness of the proposed method, the authors designed laser echo projection simulations based on the facet model and conducted field experiments. The results demonstrate that the authors achieves high-quality target contour reconstruction under varying levels of projection data missing conditions.

Abstract:The forward scattering error in water bodies is one of the primary error sources in spaceborne laser bathymetry， with individual errors potentially exceeding the depth accuracy requirements of hydrographic surveying standards. However， traditional scattering correction methods developed based on waveform information cannot be applied to the discrete photons from photon-counting lidars. In this study， a Monte Carlo simulation is used to estimate the forward scattering errors in the water column for spaceborne photon-counting lidars and an empirical formula is derived for its rapid error correction. The quantitative analysis on this correction method demonstrates that the rapid scattering error correction is practicable and reliable using the initially corrected bathymetry data of ICESat-2 and the MODIS global water backscattering coefficient at 531 nm as inputs. Further sensitivity analysis indicates that the method performance mainly depends on the uncertainty of water backscattering coefficients. With the backscattering coefficients error constrained within 20%， the empirical formula reduces the scattering error residuals to less than 0.45% of the water depth. Under four typical water conditions， the empirical formula demonstrates an average 72% reduction in water forward scattering errors， effectively eliminating the majority of scattering-induced inaccuracies. The analysis of system parameters indicates that the derived ICESat-2 correction formula can be extended to other spaceborne photon-counting bathymetric lidars through considering the receiver field-of-view radius.

Abstract:Despite rapid advancements in lidar technology， extremely long-range observation remains a significant challenge. Recently， 2μm lasers have demonstrated a potential to be applied in CDWL（Coherent Doppler Wind Lidar） system， for its high atmospheric penetration capability through the atmosphere and high potential laser power. In this study， we present a 2μm balanced detector that consists of a pair of commercial positive-intrinsic-negative （PIN） diodes with a low-noise transimpedance circuit. To meet the high bandwidth requirements， the highspeed transimpedance circuit and bias voltage tuning method were utilized to overcome the large capacitance of PIN diodes. The circuit transfer function， stability analysis and noise calculation have been studied. The detector was co-packaged with a data acquisition module for convenient data transmission and bias voltage control. The characteristics of the detector， including bandwidth， noise and bias voltage influence， are evaluated in laboratory. Results show that the RMS value of the balanced detector background noise is 539 μV and the bandwidths of the two diodes are 110.8 MHz and 110.3 MHz， respectively. The evaluation results show that the balanced detector meets the wind measurement requirements and allows for a 1.45× increase in bandwidth through bias voltage tuning. Our work offers insights into lidar detector design and bandwidth enhancement， providing a valuable reference for researchers and professionals in the field. More importantly， it lays a critical foundation for future ultra-long-range and space-borne 2μm coherent wind lidar systems by addressing key device-level challenges.

Abstract:The diffuse attenuation coefficient （Kd） is a crucial parameter in ocean optics， representing an apparent optical property influenced by the inherent optical characteristics of seawater and the surrounding light field. It is closely related to factors such as seawater quality and chlorophyll concentration. As an active remote sensing instrument， marine polarized lidar emits light in the blue-green wavelength band capable of penetrating seawater， offering all-weather detection potential， and possesses a distinct edge in mapping the vertical distribution of Kd within the ocean. By combining Fernald"s backward iteration and slope approaches， this study proposed a layered inversion method for oceanic profile Kd estimation， utilizing dual-polarization channel signals. The vertical polarization channel is specifically used to suppress surface signals and enhance near-shore oceanic backscatter. Conducted in the Yellow and East China Seas， the ocean lidar was mounted on a marine experimental platform， with a 10-meter water depth used to validate the stratification algorithm. Results show a polarization degree of 0.479 at the sea surface for the dual-polarization channel signal. With a vertical resolution of 1 meter， the stratified inversion of the oceanic profile Kd using dual-polarization channels yields a root mean square error of 0.049 compared to actual in-situ measurements， representing a 52.4% improvement in accuracy over non-polarized channel signals. Additionally， the layered inversion algorithm outperforms the traditional Fernald algorithm， demonstrating a 32.4% improvement in precision.

Abstract:In April 2022， the Atmospheric Environment Monitoring Satellite （DQ-1） was launched with its main payload Aerosol and Carbon Detection Lidar （ACDL）. The ACDL is the first spaceborne high-spectral-resolution aerosol detection lidar with great performance in aerosol profile measurement. The accuracy of ACDL was quantified （R² = 0.924） by comparing the aerosol optical depth （AOD） between ACDL and Aerosol Robotic Network （AERONET）. In March 2025， frequent dust events occurred in northern China， generating substantial quantities of dust aerosols. The spatiotemporal distribution characteristics and optical properties of dust aerosols were analyzed. The results indicated that aerosols were mainly concentrated in troposphere， with the depolarization ratio of 0.19–0.38 and the lidar ratio of 38–60 sr， exhibiting typical optical characteristics of dust. The vertical distribution demonstrates a maximum dust aerosol layer height reaching 5 km， while spatially extending over 1600 km in horizontal dimension. This study confirms the observational advantages of high-spectral-resolution detection technique from ACDL in complex aerosol environments， providing important data for atmosphere pollution research.

Abstract:Aerosol and wind field are important parameters for studying the marine atmosphere， and it is of great significance to achieve high-precision measurements. In order to realize high-temporal and spatial resolution airborne observation of atmospheric aerosols and wind fields at sea， the ship-borne atmospheric multi-parameter detection lidar has been developed. The structural design， detection principle， technical indicators and retrieval method of ship-borne atmospheric multi-parameter detection lidar are introduced. Through experimental calibration tests， the system was calibrated for atmospheric molecular Rayleigh tests and wind field observation calibration tests， which verified the observation characteristics and accuracy of the system. The experimental data of low-altitude atmospheric multi-parameter walking observation at sea carried out in the Yellow Sea and East China Sea of China on board the "Luqing Yujiao 16" test vessel in August 2024 were analyzed， and aerosol optical parameters of 0-10 km and wind field information of 0-5 km during the walking observation period were obtained. The data results show that the aerosol concentration at sea changes significantly， and there are low-level aerosol layers and low-level clouds. The atmospheric wind speed at low-level sea is basically below 20 m/s； the boundary layer height distribution fluctuates around 1 km； taking altitudes of 200 m， 500 m and 1000 m as examples， the differences in aerosol， wind speed and wind direction distribution at different altitudes on the sea are analyzed. Experimental results show that atmospheric multi-parameter detection lidar can be equipped with ocean platforms such as ships and buoys to efficiently achieve continuous and accurate observations of aerosol and wind fields over the ocean.

Abstract:A hybrid solid-state LiDAR system specifically designed for detecting rapidly rotating small celestial bodies was introduced. The ranging principle was analyzed and an imaging model was designed based on the characteristics of the fast steering mirrors and the single-photon array detector. To evaluate the performance and stability of the LiDAR system in small celestial body detection, a mapping validation method based on an outdoor terrain model simulating small celestial body features was proposed. The results show that the hybrid solid-state LiDAR system maintains high accuracy under different operating modes and power levels. In the global terrain mapping mode, the resolution was 1100×1100, and the imaging time was 0.86 s. The mapping accuracy was 2.86 cm at a distance of 100 m. In the step-scanning imaging mode, the resolution was approximately one-seventh that of the global terrain mapping mode, and the average accuracy reached 3.10 cm at distances ranging from 34 to 83 m.

Abstract:Polar regions play a crucial role in the global climate system， serving as indicators and amplifiers of climate change. Their unique geographical environment and climate processes have a significant impact on the Earth system. Laser altimetry technology， with its sub-meter or even centimeter-level measurement accuracy， has received much attention in polar research. In recent years， the number of satellites carrying laser altimetry payloads in China has gradually increased. However， there are few polar studies based on the altimetry data from Chinese satellites. This paper first verifies the polar elevation accuracy of domestic satellite laser altimetry data using reference terrain. The results demonstrate that the laser data from GF-7 and ZY-3 03 satellites achieve accuracies better than 1 meter in polar regions， while the Terrestrial Carbon Monitoring Satellite exhibits an accuracy of approximately 1.2 meters. Subsequently， laser altimetry data is employed to assist in constructing three-dimensional polar terrain from stereo imagery， with the resulting topographic products meeting the cartographic standards for 1：10，000 scale topographic maps， thereby validating the effectiveness of the composite surveying and mapping method in polar regions. Finally， multi-source laser altimetry data is integrated to calculate ice sheet surface elevation changes， revealing the application potential of domestic satellites in polar change monitoring. This study comprehensively evaluates the polar application capabilities of domestic satellite laser altimetry data from multiple perspectives， providing critical references for future large-scale polar research utilizing domestic satellite data.

Abstract:Optical detection of space target is the premise for debris collision avoidance， early warning and active removal， which is considered as the basis to safety protection of spacecraft and sustainable development of outer space activities. And lidar can achieve all-day detection and is an important supplement to passive optical payloads. This paper used detection system based on single photon detector， which had the time and position record function for the arrival signal， to measure the time-position three-dimension information of the target crossing the field-of-view of the detection system. And the twice Hough transforms were applied to determine the trajectory of the target at low SNR. The experiment results showed that the moved targets could be detected at the condition of SNR<2， and the trajectory could be determined accurately under the condition of bright background and target. This work hopes to provide reference for high sensitive detection of the dim fast target.

Abstract:Based on the flight test echo data obtained by self-developed airborne dual-frequency ocean profile LiDAR， the bathymetric error caused by wave refraction and water scattering was analyzed， and the correction method was proposed based on the combination of Genetic Algorithm （GA） and Levenberg-Marquarelt （LM） algorithm. Theoretical analysis shows that compared with the signal LM algorithm， this wave refraction correction method reduces the Root Mean Square Error （RMSE） of the inversion of sea wave profile by about 50%. The inversion method of water body optical parameters based on the seawater profile backscattering part of the measured echo signal was researched ， and the errors and influencing factors introduced in the inversion of water optical parameters based on the Fernald backward iterative integration method were theoretically analyzed， it is found that when the estimated value of the “particle laser radar ratio” deviates by a% from the true value compared to –a%， the errors in the inversion of water body diffuse attenuation coefficient and 180° volume scattering coefficient are smaller.