Data simulation of an airborne lidar system

Kim, Seong-Joon; Min, Seong-Hong; Kim, Geunhan; Lee, Impyeong; Chulmin, Jun

doi:10.1117/12.818545

Cited by 12 publications

(15 citation statements)

References 6 publications

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“…The simulator is mainly composed of three parts: geometry, radiometry, and detection, as shown in Figure 12. A geometric module identifies the source of the information of each pixel in the detector based on the geometric relationships between the LADAR system and the target [55]. It outputs the range from the perspective center to the intersection point.…”

Section: Methodsmentioning

confidence: 99%

“…The particular details of the ray-tracing used are as follows [55]. First, a grid structure was generated, and all of the facets were linked to their corresponding cells in the grid, according to the horizontal locations.…”

Section: Ladar Modeling and Simulationmentioning

confidence: 99%

“…Concept of the ray-tracing algorithm [55]. Ray-tracing algorithm used in the simulation searched the intersecting cell by recursively reducing the vertical and horizontal range until stability was achieved.…”

Section: Figurementioning

confidence: 99%

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Simulation of a Geiger-Mode Imaging LADAR System for Performance Assessment

Kim

Lee

Kwon

2013

Sensors

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As LADAR systems applications gradually become more diverse, new types of systems are being developed. When developing new systems, simulation studies are an essential prerequisite. A simulator enables performance predictions and optimal system parameters at the design level, as well as providing sample data for developing and validating application algorithms. The purpose of the study is to propose a method for simulating a Geiger-mode imaging LADAR system. We develop simulation software to assess system performance and generate sample data for the applications. The simulation is based on three aspects of modeling—the geometry, radiometry and detection. The geometric model computes the ranges to the reflection points of the laser pulses. The radiometric model generates the return signals, including the noises. The detection model determines the flight times of the laser pulses based on the nature of the Geiger-mode detector. We generated sample data using the simulator with the system parameters and analyzed the detection performance by comparing the simulated points to the reference points. The proportion of the outliers in the simulated points reached 25.53%, indicating the need for efficient outlier elimination algorithms. In addition, the false alarm rate and dropout rate of the designed system were computed as 1.76% and 1.06%, respectively.

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Section: Methodsmentioning

confidence: 99%

Section: Ladar Modeling and Simulationmentioning

confidence: 99%

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Simulation of a Geiger-Mode Imaging LADAR System for Performance Assessment

Kim

Lee

Kwon

2013

Sensors

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“…vegetation), suited for realistic simulation of LiDAR measurements from close distances and from any direction (as opposed to 2.5D elevation maps, which only allow meaningful measurements from above). A project that takes this into account is presented by Kim et al (2009). In contrast to the system described by Lohani and Mishra (2007), they use true 3D geometry to describe the scanned scene.…”

Section: Related Workmentioning

confidence: 99%

Helios: A Multi-Purpose Lidar Simulation Framework for Research, Planning and Training of Laser Scanning Operations With Airborne, Ground-Based Mobile and Stationary Platforms

Bechtold¹,

Höfle²

2016

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:In many technical domains of modern society, there is a growing demand for fast, precise and automatic acquisition of digital 3D models of a wide variety of physical objects and environments. Laser scanning is a popular and widely used technology to cover this demand, but it is also expensive and complex to use to its full potential. However, there might exist scenarios where the operation of a real laser scanner could be replaced by a computer simulation, in order to save time and costs. This includes scenarios like teaching and training of laser scanning, development of new scanner hardware and scanning methods, or generation of artificial scan data sets to support the development of point cloud processing and analysis algorithms. To test the feasibility of this idea, we have developed a highly flexible laser scanning simulation framework named Heidelberg LiDAR Operations Simulator (HELIOS). HELIOS is implemented as a Java library and split up into a core component and multiple extension modules. Extensible Markup Language (XML) is used to define scanner, platform and scene models and to configure the behaviour of modules. Modules were developed and implemented for (1) loading of simulation assets and configuration (i.e. 3D scene models, scanner definitions, survey descriptions etc.), (2) playback of XML survey descriptions, (3) TLS survey planning (i.e. automatic computation of recommended scanning positions) and (4) interactive real-time 3D visualization of simulated surveys. As a proof of concept, we show the results of two experiments: First, a survey planning test in a scene that was specifically created to evaluate the quality of the survey planning algorithm. Second, a simulated TLS scan of a crop field in a precision farming scenario. The results show that HELIOS fulfills its design goals.

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“…Figure 6 illustrates the concept of ray tracing we used. As you can see Figure 6, the cell, intersected with sub-beam, can be found by reducing the vertical and horizontal range from one to another (Kim et al, 2008). Figure 6.…”

Section: Ray-tracingmentioning

confidence: 99%

Lidar Waveform Simulation Over Complex Targets

Kim

Lee

2012

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Unlike discrete-return LIDAR system that measures the return times of some echoes, waveform LIDAR provides the full-waveform data by digitising multi-echoes. From the waveform data we can extract more information about the geometry and reflectance of the target surfaces by applying various algorithms to interpret waveform. There have been many researches about the laser beam's interaction with the illuminated surfaces and the diverse algorithms for waveform processing. The purpose of this paper is to suggest the method to simulate waveform coming from complex targets. First, we analysed the previous relevant works. And based on these we attempted to generate the simulated waveform over the complex surfaces. For the waveform simulation, we defined the subbeams spread with a consistent interval within the beam's divergence coverage. Each sub-beam has its geometry (origin and direction) and the transmitted energy considering the laser beam's profile. Then, we searched the surfaces that intersect with subbeams using ray-tracing algorithm, and computed the intersection points and the received energies. Using on the computed distance, the received energy and predefined pulse model, we generated the signals of echoes and put them together into a waveform. Finally, we completed the waveform simulation adding the signal noise. As a result of performing waveform simulation, we confirmed that the waveform data was successfully simulated by the proposed method. We believe that our method of the waveform simulation will be helpful to understand the waveform data and develop the algorithms for the waveform processing.

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Data simulation of an airborne lidar system

Cited by 12 publications

References 6 publications

Simulation of a Geiger-Mode Imaging LADAR System for Performance Assessment

Simulation of a Geiger-Mode Imaging LADAR System for Performance Assessment

Helios: A Multi-Purpose Lidar Simulation Framework for Research, Planning and Training of Laser Scanning Operations With Airborne, Ground-Based Mobile and Stationary Platforms

Lidar Waveform Simulation Over Complex Targets

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