Search Results (89)

Laser ranging technology holds a key position in the military, aerospace, and industrial fields due to its high precision and non-contact measurement characteristics. As a core component, the performance of the photon detector directly determines the ranging accuracy and range. This paper systematically reviews the technological development of photonic detectors for laser ranging, with a focus on analyzing the working principles and performance differences of traditional photodiodes [PN (P-N junction photodiode), PIN (P-intrinsic-N photodiode), and APD (avalanche photodiode)] (such as the high-frequency response characteristics of PIN and the internal gain mechanism of APD), as well as their applications in short- and medium-range scenarios. Additionally, this paper discusses the unique advantages of special structures such as transmitting junction-type and Schottky-type detectors in applications like ultraviolet light detection. This article focuses on photon counting technology, reviewing the technological evolution of photomultiplier tubes (PMTs), single-photon avalanche diodes (SPADs), and superconducting nanowire single-photon detectors (SNSPDs). PMT achieves single-photon detection based on the external photoelectric effect but is limited by volume and anti-interference capability. SPAD achieves sub-decimeter accuracy in 100 km lidars through Geiger mode avalanche doubling, but it faces challenges in dark counting and temperature control. SNSPD, relying on the characteristics of superconducting materials, achieves a detection efficiency of 95% and a dark count rate of less than 1 cps in the 1550 nm band. It has been successfully applied in cutting-edge fields such as 3000 km satellite ranging (with an accuracy of 8 mm) and has broken through the near-infrared bottleneck. This study compares the differences among various detectors in core indicators such as ranging error and spectral response, and looks forward to the future technical paths aimed at improving the resolution of photon numbers and expanding the full-spectrum detection capabilities. It points out that the new generation of detectors represented by SNSPD, through material and process innovations, is promoting laser ranging to leap towards longer distances, higher precision, and wider spectral bands. It has significant application potential in fields such as space debris monitoring. Full article

Light detection and ranging (LiDAR) sensors are essential for applications where high-resolution distance and velocity measurements are required. In particular, frequency-modulated continuous wave (FMCW) LiDAR, compared with other LiDAR implementations, provides superior receiver sensitivity, enhanced range resolution, and the capability to measure velocity. Integrating LiDARs into electronic and photonic semiconductor chips can lower their cost, size, and power consumption, making them affordable for cost-sensitive applications. Additionally, simple designs are required, such as FMCW signal generation by the direct modulation of the current of a semiconductor laser. However, semiconductor lasers are inherently nonlinear, and the driving waveform needs to be optimized to generate linear FMCW signals. In this paper, we employ pre-distortion techniques to compensate for chirp nonlinearity, achieving frequency nonlinearities of 0.0029% for the down-ramp and the up-ramp at 55 kHz. Experimental results demonstrate a highly accurate LiDAR system with a resolution of under 5 cm, operating over a 210-m range through single-mode fiber, which corresponds to approximately 308 m in free space, towards meeting the requirements for long-range autonomous driving. Full article

InGaAs/InP single-photon avalanche diodes (SPADs) are widely used in applications such as quantum information, deep-space communication, and LiDAR. However, the existence of afterpulsing effects leads to inaccuracies in the calibration of their performance, particularly in terms of photon detection efficiency (PDE). In this paper, we employ the capacitance-balancing method to achieve a 100 MHz gated InGaAs/InP SPAD and propose a time-correlated calibration method to measure its performance. The distribution of the afterpulse counts over time is predicted, enabling a valid distinction between photogenerated counts and error counts. A PDE higher than ~30% is reached with an afterpulse probability of ~15%, while the repetition frequency of the incident laser (f_laser) changes from 1 MHz to 50 MHz. A comparison of the existing methodologies for calculating PDE reveals that PDE increases with f_laser. This increase is particularly pronounced when the PDE is high. However, under the time-correlated calibration scheme employed, the PDE remains almost constant, thereby validating the reliability of the results. Full article

The laser pulse detection probability of a scanning direct time-of-flight light detection and ranging (LiDAR) measurement is evaluated based on the optical signal distribution on a multipixel single photon avalanche diode (SPAD) array. These detectors intrinsically suffer from dead-times after the successful detection of a single photon and, thus, allow only for limited counting statistics when multiple returning laser photons are imaged on a single pixel. By blurring the imaged laser spot, the transition from single-pixel statistics with high signal intensity to multipixel statistics with less signal intensity is examined. Specifically, a comparison is made between the boundary cases in which (i) the returning LiDAR signal is focused through optics onto a single pixel and (ii) the detection is performed without lenses using all available pixels on the sensor matrix. The omission of imaging optics reduces the overall system size and minimizes optical transfer losses, which is crucial given the limited laser emission power due to safety standards. The investigation relies on a photon rate model for interfering (background) and signal light, applied to a simulated first-photon sensor architecture. For single-shot scenarios that reflect the optimal use of the time budget in scanning LiDAR systems, the lens-less and blurred approaches can achieve comparable or even superior results to the focusing system. This highlights the potential of fully solid-state scanning LiDAR systems utilizing optical phase arrays or multidirectional laser chips. Full article

Accurate solar background noise modeling in island-reef LiDAR surveys is hindered by anisotropic coastal reflectivity and dynamic light paths, which isotropic models fail to address. We propose BNR-B, a bidirectional reflectance distribution function (BRDF)-based noise model that integrates solar-receiver geometry with micro-facet scattering dynamics. Validated via single-photon LiDAR field tests on diverse coastal terrains at Jiajing Island, China, BNR-B reveals the following: (1) Solar zenith/azimuth angles non-uniformly modulate noise fields—higher solar zenith angles reduce noise intensity and homogenize spatial distribution; (2) surface reflectivity linearly correlates with noise rate (R² > 0.99), while roughness governs scattering directionality through micro-facet redistribution. BNR-B achieves 28.6% higher noise calculation accuracy than Lambertian models, with a relative phase error < 2% against empirical data. As the first BRDF-derived solar noise correction framework for coastal LiDAR, it addresses critical limitations of isotropic assumptions by resolving directional noise modulation. The model’s adaptability to marine–terrestrial interfaces enhances precision in coastal monitoring and submarine mapping, offering transformative potential for geospatial applications requiring photon-counting LiDAR in complex environments. Key innovations include dynamic coupling of geometric optics and surface scattering physics, enabling robust spatiotemporal noise quantification, critical for high-resolution terrain reconstruction. Full article

Inland lakes and reservoirs are critical components of global freshwater resources. However, traditional water level monitoring stations are costly to establish and maintain, particularly in remote areas. As an alternative, satellite altimetry has become a key tool for lake water level monitoring. Nevertheless, conventional radar altimetry techniques face accuracy limitations when monitoring small water bodies. The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2), equipped with a single-photon counting lidar system, offers enhanced precision and a smaller ground footprint, making it more suitable for small-scale water body monitoring. However, the water level data obtained from the ICESat-2 ATL13 inland water surface height product are limited in quantity, while the lake water level accuracy derived from the ATL08 product is relatively low. To overcome these challenges, this study proposes a Spatial Distribution-Based Hierarchical Clustering for Photon-Counting Laser altimeter (SD-HCPLA) for enhanced water level extraction, validated through experiments conducted at the Danjiangkou Reservoir. The proposed method first employs Landsat 8/9 imagery and the Normalized Difference Water Index (NDWI) to generate a water mask, which is then used to filter ATL03 photon data within the water body boundaries. Subsequently, a Minimum Spanning Tree (MST) is constructed by traversing all photon points, where the vertical distance between adjacent photons replaces the traditional Euclidean distance as the edge length, thereby facilitating the clustering and denoising of the point cloud data. The SD-HCPLA algorithm successfully obtained 41 days of valid water level data for the Danjiangkou Reservoir, achieving a correlation coefficient of 0.99 and an average error of 0.14 m. Compared with ATL08 and ATL13, the SD-HCPLA method yields higher data availability and improved accuracy in water level estimation. Furthermore, the proposed algorithm was applied to extract water level data for five lakes and reservoirs in Hubei Province from 2018 to 2023. The temporal variations and inter-correlations of water levels were analyzed, providing valuable insights for regional ecological environment monitoring and water resource management. Full article

To address the deficiency of aircraft point cloud training data for low-altitude environment perception systems, a method termed APCG (aircraft point cloud generation) is proposed. APCG can generate aircraft point cloud data in the single photon counting Lidar (SPC-Lidar) system based on information such as aircraft type, position, and attitude. The core of APCG is the aircraft depth image generator, which is obtained through adversarial training of an improved conditional generative adversarial network (cGAN). The training data of the improved cGAN are composed of aircraft depth images formed by spatial sampling and transformation of fine point clouds of 76 types of aircraft and 4 types of drone. The experimental results demonstrate that APCG is capable of efficiently generating diverse aircraft point clouds that reflect the acquisition characteristics of the SPC-Lidar system. The generated point clouds exhibit high similarity to the standard point clouds. Furthermore, APCG shows robust adaptability and stability in response to the variation in aircraft slant range. Full article

Single-photon lidar (SPL) exhibits high sensitivity, making it particularly suitable for detecting weak echoes over long distances. However, its susceptibility to background noise necessitates the implementation of advanced filtering techniques and complex algorithms, which can significantly increase system cost and complexity. To address these challenges, we propose a time-division-multiplexing-based correlated photon lidar system that employs a narrowband pulsed laser with stable time delays and variable pulse intensities, thereby establishing temporal and intensity correlations. This all-fiber solution not only simplifies the system architecture but also enhances operational efficiency. An adaptive cross-correlation method incorporating time slicing has been developed to extract histogram signals, enabling successful 1.5 km distance measurements under intense daytime noise conditions, using a 1 s accumulation time and a 20 mm receiving aperture. The experimental results demonstrate a 38% (from 1.11 to 1.52) improvement in the signal-to-noise ratio (SNR), thereby enhancing the system’s anti-noise capability, facilitating rapid detection, and reducing overall system costs. Full article

The development of a correlation-assisted direct time-of-flight (CA-dToF) pixel provides a novel solution for time-of-flight applications that combines low power consumption, robust ambient shot noise suppression, and a compact design. However, the pixel’s implementation introduces systematic errors, affecting its performance. We investigate the pixel’s robustness against various noise sources, including timing jitter, kTC noise, switching noise, and photon shot noise. Additionally, we address limitations such as the SPAD deadtime, and source follower gain mismatch and offset, identifying their impact on performance. The paper also proposes solutions to enhance the pixel’s overall reliability and to improve the pixel’s implementation. Full article

In order to solve the problem of detecting, tracking and estimating the size of “low, slow and small” targets (such as UAVs) in the air, this paper designs a single-photon LiDAR imaging system based on Geiger-mode Avalanche Photodiode (Gm-APD). It improves the Mean-Shift algorithm and proposes an automatic tracking method that combines the weighted centroid method to realize target extraction, and the principal component analysis (PCA) method of the adaptive rotating rectangle is realized to fit the flight attitude of the target. This method uses the target intensity and distance information provided by Gm-APD LiDAR. It addresses the problem of automatic calibration and size estimation under multiple flight attitudes. The experimental results show that the improved algorithm can automatically track the targets in different flight attitudes in real time and accurately calculate their sizes. The improved algorithm is stable in the 1250-frame tracking experiment of DJI Elf 4 UAV with a flying speed of 5 m/s and a flying distance of 100 m. Among them, the fitting error of the target is always less than 2 pixels, while the size calculation error of the target is less than 2.5 cm. This shows the remarkable advantages of Gm-APD LiDAR in detecting “low, slow and small” targets. It is of practical significance to comprehensively improve the ability of UAV detection and C-UAS systems. However, the application of this technology in complex backgrounds, especially in occlusion or multi-target tracking, still faces certain challenges. In order to realize long-distance detection, further optimizing the field of view of the Gm-APD single-photon LiDAR is still a future research direction. Full article

For the demand for long-range and high-resolution target reconstruction of slow-moving small underwater targets, research on single-photon lidar target reconstruction technology is being carried out. This paper reports the sequential multimodal underwater single-photon lidar adaptive target reconstruction algorithm based on spatiotemporal sequence fusion, which has strong information extraction and noise filtering ability and can reconstruct the target depth and reflective intensity information from complex echo photon time counts and spatial pixel relationships. The method consists of three steps: data preprocessing, sequence-optimized extreme value inference filtering, and collaborative variation strategy for image optimization to achieve high-quality target reconstruction in complex underwater environments. Simulation and test results show that the target reconstruction method outperforms the current imaging algorithms, and the built single-photon lidar system achieves underwater lateral and distance resolution of 5 mm and 2.5cm@6AL, respectively. This indicates that the method has a great advantage in sparse photon counting imaging and possesses the capability of underwater target imaging under the background of strong light noise. It also provides a good solution for underwater target imaging of small slow-moving targets with long-distance and high-resolution. Full article

Single-Photon Avalanche Photodiodes (SPADs) are increasingly utilized in high-temperature-operated, high-performance Light Detection and Ranging (LiDAR) systems as well as in ultra-low-temperature-operated quantum science applications due to their high photon sensitivity and timing resolution. Consequently, the jitter value of SPADs at different temperatures plays a crucial role in LiDAR systems and Quantum Key Distribution (QKD) applications. However, limited studies have been conducted on this topic. In this study, we analyze the jitter characteristics of SPAD devices, focusing on the influence of device structures in two SPAD designs fabricated using the TSMC 18HV and TSMC 13HV processes. Using picosecond lasers with wavelengths ranging from ultraviolet (405 nm) to near-infrared (905 nm), we investigate the impact of different diffusion carrier types on jitter values and their temperature dependence across a range of 0 °C to 60 °C. Our results show that the jitter value of SPAD devices with low electric field regions varies significantly with temperature. This variation can be attributed to the higher temperature-dependent diffusion constant, as demonstrated by fitting the jitter diffusion tail with two diffusion time constants. In contrast, SPADs designed with modified electric field distributions exhibit smaller diffusion time constants and weaker temperature dependence, resulting in a much smaller temperature-dependent jitter value. Full article

Traditional LiDAR and air-medium-based single-photon LiDAR struggle to perform effectively in high-scattering environments. The laser beams are subject to severe medium absorption and multiple scattering phenomena in such conditions, greatly limiting the maximum operational range and imaging quality of the system. The high sensitivity and high temporal resolution of single-photon LiDAR enable high-resolution depth information acquisition under limited illumination power, making it highly suitable for operation in environments with extremely poor visibility. In this study, we focus on the data distribution characteristics of active single-photon LiDAR operating underwater, without relying on time-consuming deep learning frameworks. By leveraging the differences in time-domain distribution between noise and echo signals, as well as the hidden spatial information among echo signals from different pixels, we rapidly obtain imaging results across various distances and attenuation coefficients. We have experimentally verified that the proposed spatial sequential matching enhanced (SSME) algorithm can effectively enhance the reconstruction quality of reflection intensity maps and depth maps in strong scattering underwater environments. Through additional experiments, we demonstrated the algorithm’s reconstruction effect on different geometric shapes and the system’s resolution at different distances. This rapidly implementable reconstruction algorithm provides a convenient way for researchers to preview data during underwater single-photon LiDAR studies. Full article

Lidar technology plays a pivotal role in lunar exploration, particularly in terrain mapping, 3D topographic surveying, and velocity measurement, which are crucial for guidance, navigation, and control. This paper reviews the current global research and applications of lidar technology in lunar missions, noting that existing efforts are primarily focused on 3D terrain mapping and velocity measurement. The paper also discusses the detailed system design and key results of the laser altimeter, laser ranging sensor, laser 3D imaging sensor, and laser velocity sensor used in the Chang’E lunar missions. By comparing and analyzing similar foreign technologies, this paper identifies future development directions for lunar laser payloads. The evolution towards multi-beam single-photon detection technology aims to enhance the point cloud density and detection efficiency. This manuscript advocates that China actively advance new technologies and conduct space application research in areas such as multi-beam single-photon 3D terrain mapping, lunar surface water ice measurement, and material composition analysis, to elevate the use of laser pay-loads in lunar and space exploration. Full article

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. Full article