Simulation and Design of Circular Scanning Airborne Geiger Mode Lidar for High-Resolution Topographic Mapping

Liu, Fanghua; He, Yan; Chen, Weibiao; Luo, Yuan; Yu, Jiangying; Chen, Yongqiang; Jiao, Chongmiao; Liu, Meizhong

doi:10.3390/s22103656

Cited by 4 publications

(2 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Thus, the method proposed in the paper can fully utilize the waveforms to better extract weak seafloor signals, which, in turn, improves the seafloor point clouds' completeness and reduces the artifacts generated in the seafloor's DEM. In addition to the weak echo signal of laser echoes in the ocean, the same problem exists for the LIDAR waveform on land, where airborne LIDAR applications include archaeological research, power patrols, and topographic mapping [23][24][25]. Although the atmospheric attenuation of laser energy is much less than that of seawater, the ground echoes located under trees also suffer from weak echoes that are not easily detected due to multiple reflections of the laser from the tree canopy [26].…”

Section: Discussionmentioning

confidence: 99%

Faint Echo Extraction from ALB Waveforms Using a Point Cloud Semantic Segmentation Model

Huang

Zhu

et al. 2023

Remote Sensing

Self Cite

View full text Add to dashboard Cite

As an active remote sensing technology, airborne LIDAR can work at all times while emitting specific wavelengths of laser light that can penetrate seawater. Airborne LIDAR bathymetry (ALB) records an object’s full return waveform, including the water surface, water column, seafloor, and the objects on it. Due to the seawater’s absorption and scattering and the seafloor’s reflectivity effect, the seafloor’s amplitude of seafloor echoes varies greatly. Seafloor echoes with low signal-to-noise ratios are not easily detected using waveform processing methods, which can lead to insufficient seafloor topography depth and incomplete seafloor topography coverage. To extract faint seafloor echoes, we proposed a depth extraction method based on the PointConv deep learning model, called FWConv. The method assumed that spatially adjacent echoes were correlated. We converted all the spatially adjacent multi-frame waveforms into a point cloud. Each point represented a bin value in the waveform, and the points’ properties contained spatial coordinates and the amplitude in the waveform. In the semantic segmentation of these point clouds using deep learning models, we considered not only each centroid’s amplitude, but also its neighboring points’ distance and amplitude. This enriched the centroids’ features and allowed the model to better discriminate between background noise and seafloor echoes. The results showed that FWConv could extract faint seafloor echoes in the experimental area and was not easily affected by noise, and that the correctness reached 99.82%. The number of point clouds increased by 158%, and the seafloor elevation accuracy reached 0.20 m concerning the multibeam echo sounder data.

show abstract

Section: Discussionmentioning

confidence: 99%

Faint Echo Extraction from ALB Waveforms Using a Point Cloud Semantic Segmentation Model

Huang

Zhu

et al. 2023

Remote Sensing

Self Cite

View full text Add to dashboard Cite

show abstract

“…Therefore, there is an increasing demand for advanced underwater detection technology to support marine survey activities. Light Detection and Ranging (Lidar), as a widely used active remote sensing technique, has been extensively used in various fields, including topographic mapping [3], bathymetry [4], atmospheric remote sensing [5], forest management [6], and underwater target detection [7].…”

Section: Introductionmentioning

confidence: 99%

Simulation and Design of an Underwater Lidar System Using Non-Coaxial Optics and Multiple Detection Channels

Chen

Guo

et al. 2023

Remote Sensing

Self Cite

View full text Add to dashboard Cite

The efficacy of underwater laser detection is considerably impacted by the intense attenuation of light resulting from the scattering and absorption effects of water. In this study, we present the simulation and design of the underwater Lidar system that integrates the paraxial multi-channel detection strategy to enhance the dynamic range in subsea environments. To evaluate the performance of the system with multiple detection channels, we introduce a multi-channel underwater Lidar simulation (MULS) method based on the radiative transfer Lidar equations. Experimental validations were conducted under varied water conditions to assess the performance of the prototype and validate the simulation results. The measured range accuracy of each channel in the prototype is better than 0.1085 m, and the simulated and measured waveforms exhibit strong correlations, verifying the reliability and validity of the simulation method. The effects of transceiver configuration and the maximum detectable range of different detection methods were also discussed. Preliminary results indicate that the paraxial multi-channel design effectively suppresses near-field backscattering and substantially enhances the maximum detectable range. The findings presented in this study may provide valuable insights for the design and optimization of future underwater laser detection systems.

show abstract

Airborne single-photon LiDAR towards a small-sized and low-power payload

Hong,

Liu,

et al. 2024

Optica

View full text Add to dashboard Cite

Single-photon light detection and ranging (LiDAR) has played an important role in areas ranging from target identification and 3D imaging to remote sensing. Its high sensitivity provides the feasibility of lightweight LiDAR systems for the resource-limited airborne and spaceborne platforms. Here, we design and demonstrate an airborne single-photon LiDAR towards the compact, small-sized, and low-power payload. To reduce the system size, we utilize small telescopes with an optical aperture of 47 mm and develop the sub-pixel scanning approach to enhance the imaging resolution. With the fine scanning mirrors, we validate the super-resolution ability in the ground experiment by surpassing the system’s resolution by 2.5 times and achieve high-resolution 3D imaging in the airborne experiment. To realize low-power LiDAR, we employ photon-efficient computational algorithms and high-quality single-photon avalanche diode (SPAD) arrays. This enables us to reconstruct images from noisy data even under challenging conditions of two signal photons per pixel. Using the airborne single-photon LiDAR system, we demonstrate 3D imaging during daytime over a large area for remote sensing applications and show the capability to reveal the detailed features of various landforms and objects.

show abstract

Simulation and Design of Circular Scanning Airborne Geiger Mode Lidar for High-Resolution Topographic Mapping

Cited by 4 publications

References 22 publications

Faint Echo Extraction from ALB Waveforms Using a Point Cloud Semantic Segmentation Model

Faint Echo Extraction from ALB Waveforms Using a Point Cloud Semantic Segmentation Model

Simulation and Design of an Underwater Lidar System Using Non-Coaxial Optics and Multiple Detection Channels

Airborne single-photon LiDAR towards a small-sized and low-power payload

Contact Info

Product

Resources

About