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LiDAR Sensor Hardware, Algorithm Development and Its Application

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Radar Sensors".

Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 23234

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Prof. Dr. Dong Liu

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Guest Editor

Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China
Interests: lidar system and algorithm development; multi-sensors remote sensing; airborne and satellite lidar remote sensing

Prof. Dr. Zhizhong Kang

E-Mail Website
Guest Editor

Department of Remote Sensing and Geo-Information Engineering, School of Land Science and Technology, China University of Geosciences in Beijing, Xueyuan Road 29, Haidian District, Beijing 100083, China
Interests: digital photogrammetry and computer vision; processing of indoor, terrestrial and air-borne LiDAR data; indoor 3D modeling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Lidar is an acronym for light detection and ranging, which originated in atmosphere monitoring before the invention of laser. In 1960, the laser was invented with four unique characteristics, coherence, directionality, monochromatic, and high intensity, which greatly enhanced the capability of the lidar remote sensing in atmospheric physics and chemistry research. Lidar can also measure the distance and can be carried on the airborne and spaceborne platform to study the surface elevations and bathymetric mapping as well. This application subsequently expands to vegetation classification, land cover use, and terrestrial scanning, as well as architecture scanning and micro-topography. Recently, according to the outburst demands of autopilot technology, lidar is regarded as the most effective sensor to detect the presence of vehicles, pedestrians, and other relevant entities, and has been manufactured in commercial vehicles. This Special Issue invites contributions on the cutting-edge lidar technology developments, including the hardware design and production, the robust algorithm and complex scenario, and the work to discover the advantages of the lidar sensors in various application fields.

Potential topics include, but are not limited to:

Lidar system and algorithm development for atmosphere monitoring on environmental and climate studies;
Lidar sensing mapping and application in elevation measurement, ecological and land classification, precision forestry and agriculture, natural disaster and civil facility monitoring, micro-topography, etc.;
Automatic driving lidar, algorithms for object detection and identification and 3D modeling;
New technology and device for lidar sensors.

Prof. Dr. Dong Liu
Prof. Dr. Zhizhong Kang
Guest Editors

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Keywords

atmosphere monitoring
surveying and mapping
automatic driving
SLAM
MEMS
sensor calibration
multisensory fusion
data quality control/evaluation
optical phased array
3D modeling
ecological and land classification
precision forestry and agriculture
natural disaster monitoring
civil facility safety monitoring
object detection and identification

Published Papers (11 papers)

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Research

11 pages, 4019 KiB

Open AccessArticle

Original and Low-Cost ADS-B System to Fulfill Air Traffic Safety Obligations during High Power LIDAR Operation

by Frédéric Peyrin, Patrick Fréville, Nadège Montoux and Jean-Luc Baray

Sensors 2023, 23(6), 2899; https://doi.org/10.3390/s23062899 - 07 Mar 2023

Cited by 1 | Viewed by 1549

Abstract

LIDAR is an atmospheric sounding instrument based on the use of high-power lasers. The use of these lasers involves fulfilling obligations with respect to air safety. In this article, we present a low-cost air traffic surveillance solution integrated into an automated operating system for the Rayleigh-Mie-Raman LIDAR of Clermont Ferrand and the statistical elements of its application over more than two years of operation from September 2019 to March 2022. Air traffic surveillance that includes the possibility of shutting off lasers is required by international regulations because LIDAR is equipped with a class four laser that presents potential dangers to aircraft flying overhead. The original system presented in this article is based on software-defined radio. ADS-B transponder frames are analyzed in real-time, and laser emission is stopped during LIDAR operation when an aircraft is detected within a 2 km radius around the LIDAR. The system was accredited in 2019 by the French air traffic authorities. Laser shutdowns due to the detection of aircraft near the Clermont Ferrand LIDAR caused a data loss rate of less than 2% during the period of application. Full article

(This article belongs to the Special Issue LiDAR Sensor Hardware, Algorithm Development and Its Application)

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23 pages, 5739 KiB

Open AccessArticle

Extracting Traffic Signage by Combining Point Clouds and Images

by Furao Zhang, Jianan Zhang, Zhihong Xu, Jie Tang, Peiyu Jiang and Ruofei Zhong

Sensors 2023, 23(4), 2262; https://doi.org/10.3390/s23042262 - 17 Feb 2023

Viewed by 1731

Abstract

Recognizing traffic signs is key to achieving safe automatic driving. With the decreasing cost of LiDAR, the accurate extraction of traffic signs using point cloud data has received wide attention. In this study, we propose combining point cloud and image traffic sign extraction: firstly, we use the improved YoloV3 model to detect traffic signs in panoramic images. The specific improvement is that the convolution block attention module is added to the algorithm framework, the traditional K-means clustering algorithm is improved, and Focal Loss is introduced as the loss function. It shows higher accuracy on the TT100K dataset, with a 1.4% improvement in accuracy compared to the previous YoloV3. Then, the point cloud of the area where the traffic sign is located is extracted by combining the image detection results. On this basis, the outline of the traffic sign is accurately extracted using the reflection intensity, spatial geometry and other information. Compared with the traditional method, the proposed method can effectively reduce the missed detection rate, narrow the range of point cloud, and improve the detection accuracy by 10.2%. Full article

(This article belongs to the Special Issue LiDAR Sensor Hardware, Algorithm Development and Its Application)

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16 pages, 9123 KiB

Open AccessArticle

Parameter Optimization and Development of Mini Infrared Lidar for Atmospheric Three-Dimensional Detection

by Zhiqiang Kuang, Dong Liu, Decheng Wu, Zhenzhu Wang, Cheng Li and Qian Deng

Sensors 2023, 23(2), 892; https://doi.org/10.3390/s23020892 - 12 Jan 2023

Cited by 1 | Viewed by 1752

Abstract

In order to conduct more thorough research on the structural characteristics of the atmosphere and the distribution and transmission of atmospheric pollution, the use of remote sensing technology for multi-dimensional detection of the atmosphere is needed. A light-weight, low-volume, low-cost, easy-to-use and low-maintenance mini Infrared Lidar (mIRLidar) sensor is developed for the first time. The model of lidar is established, and the key optical parameters of the mIRLidar are optimized through simulation, in which wavelength of laser, energy of pulse laser, diameter of telescope, field of view (FOV), and bandwidth of filter are included. The volume and weight of the lidar system are effectively reduced through optimizing the structural design and designing a temperature control system to ensure the stable operation of the core components. The mIRLidar system involved a 1064 nm laser (the pulse laser energy 15 μJ, the repetition frequency 5 kHz), a 100 mm aperture telescope (the FOV 1.5 mrad), a 0.5 nm bandwidth of filter and an APD, where the lidar has a volume of 200 mm × 200 mm × 420 mm and weighs about 13.5 kg. It is shown that the lidar can effectively detect three-dimensional distribution and transmission of aerosol and atmospheric pollution within a 5 km detection range, from Horizontal, scanning and navigational atmospheric measurements. It has great potential in the field of meteorological research and environmental monitoring. Full article

(This article belongs to the Special Issue LiDAR Sensor Hardware, Algorithm Development and Its Application)

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22 pages, 29366 KiB

Open AccessArticle

CMANet: Cross-Modality Attention Network for Indoor-Scene Semantic Segmentation

by Longze Zhu, Zhizhong Kang, Mei Zhou, Xi Yang, Zhen Wang, Zhen Cao and Chenming Ye

Sensors 2022, 22(21), 8520; https://doi.org/10.3390/s22218520 - 05 Nov 2022

Cited by 7 | Viewed by 2082

Abstract

Indoor-scene semantic segmentation is of great significance to indoor navigation, high-precision map creation, route planning, etc. However, incorporating RGB and HHA images for indoor-scene semantic segmentation is a promising yet challenging task, due to the diversity of textures and structures and the disparity of multi-modality in physical significance. In this paper, we propose a Cross-Modality Attention Network (CMANet) that facilitates the extraction of both RGB and HHA features and enhances the cross-modality feature integration. CMANet is constructed under the encoder–decoder architecture. The encoder consists of two parallel branches that successively extract the latent modality features from RGB and HHA images, respectively. Particularly, a novel self-attention mechanism-based Cross-Modality Refine Gate (CMRG) is presented, which bridges the two branches. More importantly, the CMRG achieves cross-modality feature fusion and produces certain refined aggregated features; it serves as the most crucial part of CMANet. The decoder is a multi-stage up-sampled backbone that is composed of different residual blocks at each up-sampling stage. Furthermore, bi-directional multi-step propagation and pyramid supervision are applied to assist the leaning process. To evaluate the effectiveness and efficiency of the proposed method, extensive experiments are conducted on NYUDv2 and SUN RGB-D datasets. Experimental results demonstrate that our method outperforms the existing ones for indoor semantic-segmentation tasks. Full article

(This article belongs to the Special Issue LiDAR Sensor Hardware, Algorithm Development and Its Application)

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18 pages, 8003 KiB

Open AccessArticle

Weighted Iterative CD-Spline for Mitigating Occlusion Effects on Building Boundary Regularization Using Airborne LiDAR Data

by Renato César dos Santos, Ayman F. Habib and Mauricio Galo

Sensors 2022, 22(17), 6440; https://doi.org/10.3390/s22176440 - 26 Aug 2022

Cited by 1 | Viewed by 1197

Abstract

Building occlusions usually decreases the accuracy of boundary regularization. Thus, it is essential that modeling methods address this problem, aiming to minimize its effects. In this context, we propose a weighted iterative changeable degree spline (WICDS) approach. The idea is to use a weight function for initial building boundary points, assigning a lower weight to the points in the occlusion region. As a contribution, the proposed method allows the minimization of errors caused by the occlusions, resulting in a more accurate contour modeling. The conducted experiments are performed using both simulated and real data. In general, the results indicate the potential of the WICDS approach to model a building boundary with occlusions, including curved boundary segments. In terms of F_score and PoLiS, the proposed approach presents values around 99% and 0.19 m, respectively. Compared with the previous iterative changeable degree spline (ICDS), the WICDS resulted in an improvement of around 6.5% for completeness, 4% for F_score, and 0.24 m for the PoLiS metric. Full article

(This article belongs to the Special Issue LiDAR Sensor Hardware, Algorithm Development and Its Application)

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17 pages, 5725 KiB

Open AccessArticle

New Denoising Method for Lidar Signal by the WT-VMD Joint Algorithm

by Zhenzhu Wang, Hongbo Ding, Bangxin Wang and Dong Liu

Sensors 2022, 22(16), 5978; https://doi.org/10.3390/s22165978 - 10 Aug 2022

Cited by 4 | Viewed by 1972

Abstract

Light detection and ranging (LIDAR) is an active remote sensing system. Lidar echo signal is non-linear and non-stationary, which is often accompanied by various noises. In order to filter out the noise and extract valid signal information, a suitable method should be chosen for noise reduction. Some denoising methods are commonly used, such as the wavelet transform (WT), the empirical mode decomposition (EMD), the variational mode decomposition (VMD), and their improved algorithms. In this paper, a new denoising method named the WT-VMD joint algorithm based on the sparrow search algorithm (SSA), for lidar signal is selected by comparative experiment analysis. It is shown that this method is the most suitable one with the maximum signal-to-noise ratio (SNR), the minimum root-mean-square error (RMSE), and a relatively small indicator of smoothness when it is used in three kinds (50, 100, and 1000 pulses) of simulate lidar signals. The SNR is increased by 138.5%, 77.8% and 42.8% and the RMSE is decreased by 81.8%, 72.0% and 68.8% when being used to the three kinds of cumulative signal without pollution. Then, the SNR is increased by 83.3%, 60.4% and 24.0% and the RMSE is decreased by 70.8%, 66.0% and 50.5% when being used to the three kinds of cumulative signal with aerosol and clouds. The WT-VMD joint algorithm based on SSA is used in the denoising process for the actual lidar signal, showing extraordinary denoising effect and will improve the inversion accuracy of the lidar signal. Full article

(This article belongs to the Special Issue LiDAR Sensor Hardware, Algorithm Development and Its Application)

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14 pages, 4584 KiB

Open AccessArticle

Analysis of the Impact of Changes in Echo Signal Parameters on the Uncertainty of Distance Measurements in p-ToF Laser Rangefinders

by Michał Muzal and Marek Zygmunt

Sensors 2022, 22(16), 5973; https://doi.org/10.3390/s22165973 - 10 Aug 2022

Cited by 1 | Viewed by 1183

Abstract

The article presents results of research on the influence of changes in parameters of the digitally recorded echo signals on the uncertainty of pulsed Time-of-Flight (p-ToF) laser distance measurements. The main objective of the study was to evaluate the distance calculation method developed by the authors. This method is based on the acquisition of the full-waveform of the echo pulse signal and approximation of its shape by the second-degree polynomial (we called it SDPA for short). To determine the pulse transit time and measure the distance, the position of the vertex of this parabola is sought. This position represents the maximum intensity of the incoming echo signal and is related to the round-trip propagation time of the laser pulse. In the presented work, measurement uncertainty was evaluated using simulation tests for various parameters of the echo pulse. All obtained results were used to formulate the general relationship between the measurement uncertainty of the SDPA algorithm and the parameters of the received echo signals. This formula extends the base knowledge in the domain of laser p-ToF distance measurements. It can be used to estimate the measurement uncertainty of a FW LiDAR at an early design stage. This greatly improves capabilities of analysis of expected performance of the device. It can also be implemented directly into the rangefinder’s measurement algorithm to estimate the measurement uncertainty based on the emission of a single pulse rather than a series of pulses. Full article

(This article belongs to the Special Issue LiDAR Sensor Hardware, Algorithm Development and Its Application)

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18 pages, 53674 KiB

Open AccessArticle

ScatterHough: Automatic Lane Detection from Noisy LiDAR Data

by Honghao Zeng, Shihong Jiang, Tianxiang Cui, Zheng Lu, Jiawei Li, Boon-Giin Lee, Junsong Zhu and Xiaoying Yang

Sensors 2022, 22(14), 5424; https://doi.org/10.3390/s22145424 - 20 Jul 2022

Cited by 1 | Viewed by 2736

Abstract

Lane detection plays an essential role in autonomous driving. Using LiDAR data instead of RGB images makes lane detection a simple straight line, and curve fitting problem works for realtime applications even under poor weather or lighting conditions. Handling scatter distributed noisy data is a crucial step to reduce lane detection error from LiDAR data. Classic Hough Transform (HT) only allows points in a straight line to vote on the corresponding parameters, which is not suitable for data in scatter form. In this paper, a Scatter Hough algorithm is proposed for better lane detection on scatter data. Two additional operations,

ρ

neighbor voting and

ρ

neighbor vote-reduction, are introduced to HT to make points in the same curve vote and consider their neighbors’ voting result as well. The evaluation of the proposed method shows that this method can adaptively fit both straight lines and curves with high accuracy, compared with benchmark and state-of-the-art methods. Full article

(This article belongs to the Special Issue LiDAR Sensor Hardware, Algorithm Development and Its Application)

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15 pages, 5730 KiB

Open AccessArticle

Design of Lidar Data Acquisition and Control System in High Repetition Rate and Photon-Counting Mode: Providing Testing for Space-Borne Lidar

by Liangliang Cheng, Chenbo Xie, Ming Zhao, Lu Li, Hao Yang, Zhiyuan Fang, Jianfeng Chen, Dong Liu and Yingjian Wang

Sensors 2022, 22(10), 3706; https://doi.org/10.3390/s22103706 - 12 May 2022

Cited by 3 | Viewed by 3827

Abstract

For ground-based lidars in atmospheric observation, their data acquisition unit and control unit usually work independently. They usually require the cooperation of large-volume, high-power-consumption Industrial Personal Computer (IPC). However, the space-borne lidar has high requirements on the stability and integration of the acquisition control system. In this paper, a new data acquisition and lidar control system (DALCS) was developed based on System-on-Chip Field-Programmable Gate Array (SoC FPGA) technology. It can be used in lidar systems with high repetition rate and photon-counting mode and has functions such as data storage, laser control, automatic collimation, wireless communication, and fault self-test. DALCS has two working modes: in online mode, the echo data collected by DALCS are transmitted to the computer for display in real-time and then stored with the current time as the file name; in offline mode, the data are stored in local non-volatile memory, which can be read remotely and can work autonomously when there is no IPC. The test results showed that in the frequency range of 0–70 M, the counting linearity of DALCS reached 0.9999, and the maximum relative error between the DALCS card and the standard signal source was 0.211%. The comparison results showed that the correlation coefficient between DALCS and MCS-PCI was as high as 0.99768. The DALCS was placed in a self-developed lidar sensor system for continuous observation, and the system worked stably under different weather conditions. The range-squared-corrected signal profiles obtained from the observations reflect the spatial and temporal distribution characteristics of aerosols and clouds well. This provides scheme verification and experimental support for the development of space-borne lidar data acquisition and control system. Full article

(This article belongs to the Special Issue LiDAR Sensor Hardware, Algorithm Development and Its Application)

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11 pages, 2572 KiB

Open AccessArticle

Simultaneous Extraction of Planetary Boundary-Layer Height and Aerosol Optical Properties from Coherent Doppler Wind Lidar

by Yehui Chen, Xiaomei Jin, Ningquan Weng, Wenyue Zhu, Qing Liu and Jie Chen

Sensors 2022, 22(9), 3412; https://doi.org/10.3390/s22093412 - 29 Apr 2022

Cited by 4 | Viewed by 1356

Abstract

Planetary boundary-layer height is an important physical quantity for weather forecasting models and atmosphere environment assessment. A method of simultaneously extracting the surface-layer height (SLH), mixed-layer height (MLH), and aerosol optical properties, which include aerosol extinction coefficient (AEC) and aerosol optical depth (AOD), based on the signal-to-noise ratio (SNR) of the same coherent Doppler wind lidar (CDWL) is proposed. The method employs wavelet covariance transform to locate the SLH and MLH using the local maximum positions and an automatic algorithm of dilation operation. AEC and AOD are determined by the fitting curve using the SNR equation. Furthermore, the method demonstrates the influential mechanism of optical properties on the SLH and MLH. MLH is linearly correlated with AEC and AOD because of solar heating increasing. The results were verified by the data of an ocean island site in China. Full article

(This article belongs to the Special Issue LiDAR Sensor Hardware, Algorithm Development and Its Application)

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18 pages, 4637 KiB

Open AccessArticle

Simulation and Analysis of Mie-Scattering Lidar-Measuring Atmospheric Turbulence Profile

by Yuqing Lu, Jiandong Mao, Yingnan Zhang, Hu Zhao, Chunyan Zhou, Xin Gong, Qiang Wang and Yi Zhang

Sensors 2022, 22(6), 2333; https://doi.org/10.3390/s22062333 - 17 Mar 2022

Cited by 2 | Viewed by 2346

Abstract

Based on the residual turbulent scintillation theory, the Mie-scattering lidar can measure the intensity of atmospheric turbulence by detecting the light intensity scintillation index of the laser return signal. In order to evaluate and optimize the reliability of the Mie-scattering lidar system for detecting atmospheric turbulence, the appropriate parameters of the Mie-scattering lidar system are selected and optimized using the residual turbulent scintillation theory. Then, the Fourier transform method is employed to perform the numerical simulation of the phase screen of the laser light intensity transformation on the vertical transmission path of atmospheric turbulence. The phase screen simulation, low-frequency optimization, and scintillation index calculation methods are provided in detail, respectively. Based on the phase distribution of the laser beam, the scintillation index is obtained. Through the relationship between the scintillation index and the atmospheric turbulent refractive index structure constant, the atmospheric turbulence profile is inverted. The simulation results show that the atmospheric refractive index structure constant profile obtained by the iterative method is consistent with the input HV_5/7 model below 6500 m, which has great guiding significance to carry out actual experiments to measure atmospheric turbulence using the Mie lidar. Full article

(This article belongs to the Special Issue LiDAR Sensor Hardware, Algorithm Development and Its Application)

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