Overview

LiDAR is one of many active sensor technologies that uses electromagnetic radiation. Operating in the optical and infrared wavelengths, it is similar to more-familiar passive EO/IR sensor technology. It is also similar to radar in that it uses reflected electromagnetic radiation emitted by the sensor. LiDAR is commonly used for making high-resolution maps and has applications in geodesy, geomatics, archaeology, geography, geology, geomorphology, seismology, forestry, atmospheric physics, laser guidance, airborne laser swath mapping, and laser altimetry. It is also being used for control and navigation of some autonomous cars. The first part of LiDAR Technologies and Systems introduces LiDAR and its history, and then covers the LiDAR range equation and the link budget (how much signal a LiDAR must emit in order to get a certain number of reflected photons back), as well as the rich phenomenology of LiDAR, which results in a diverse array of LiDAR types. The middle chapters discuss the components of a LiDAR system, including laser sources and modulators, LiDAR receivers, beam-steering approaches, and LiDAR processing. The last part covers testing, performance metrics, and significant applications, including how to build systems for some of the more popular applications.

Full Product Details

Author:   Paul F. McManamon
Publisher:   SPIE Press
Imprint:   SPIE Press
Weight:   1.375kg
ISBN:  

9781510625396

ISBN 10:   1510625399
Pages:   520
Publication Date:   30 July 2019
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

Preface 1 Introduction to LiDAR 1.1 Context of LiDAR 1.2 Conceptual Discussion of LiDAR 1.3 Terms for Active EO Sensing 1.4 Types of LiDARs 1.4.1 Some LiDARs for surface-scattering (hard) targets 1.4.2 Some LiDARS for volume-scattering (soft) targets 1.5 LiDAR Detection Modes 1.6 Flash LiDAR versus Scanning LiDAR 1.7 Eye Safety Considerations 1.8 Laser Safety Categories 1.9 Monostatic versus Bistatic LiDAR 1.10 Transmit/Receive Isolation 1.11 Major Devices in a LiDAR 1.11.1 Laser sources 1.11.2 Receivers 1.11.3 Apertures 1.12 Organization of this Book Problems and Solutions References 2 History of LiDAR 2.1 Rangefinders, Altimeters, and Designators 2.1.1 First steps of rangerfinders 2.1.2 Long-distance rangefinders 2.1.3 Laser altimeters 2.1.4 Laser designators 2.1.5 Obstacle avoidance applications 2.2 Early Coherent LiDARs 2.2.1 Early work at MIT Lincoln Lab 2.2.2 Early coherent LiDAR airborne applications 2.2.3 Autonomous navigation using coherent LiDAR 2.2.4 Atmospheric wind sensing 2.2.5 Laser vibrometry 2.2.6 Synthetic-aperture LiDAR 2.3 Early Space-based LiDAR 2.4 Flight-based Laser Vibrometers 2.5 Environmental LiDARs 2.5.1 Early steps 2.5.2 Multiwavelength LiDARs 2.5.3 LiDAR sensing in China 2.5.4 LiDAR sensing in Japan 2.6 Imaging LiDARs 2.6.1 Early LiDAR imaging 2.6.2 Imaging LiDARs for manufacturing 2.6.3 Range-gated imaging programs 2.6.4 3D LiDAR 2.6.5 Imaging for weapon guidance 2.6.6 Flash-imaging LiDAR 2.6.7 Mapping LiDAR 2.6.8 LiDARs for underwater: laser-based bathymetry 2.6.9 Laser micro-radar 2.7 History Conclusion References 3 LiDAR Range Equation 3.1 Introduction to the LiDAR Range Equation 3.2 Illuminator Beam 3.3 LiDAR Cross-Section 3.3.1 Cross-section of a corner cube 3.4 Link Budget Range Equation 3.5 Atmospheric Effects 3.5.1 Atmospheric scattering 3.5.2 Atmospheric turbulence 3.5.3 Aero-optical effects on LiDAR 3.5.4 Extended (deep) turbulence 3.5.5 Speckle Problems and Solutions References 4 Types of LiDAR 4.1 Direct-Detection LiDAR 4.1.1 1D range-only LiDAR 4.1.2 Tomographic imaging LiDAR 4.1.3 Range-gated active imaging (2D LiDAR) 4.1.4 3D scanning LiDAR 4.1.5 Flash imaging 4.1.6 3D mapping applications 4.1.7 Laser-induced breakdown spectroscopy 4.1.8 Laser-induced fluorescence 4.1.9 Active multispectral LiDAR 4.1.10 LiDARs using polarization as a discriminant 4.2 Coherent LiDAR 4.2.1 Laser vibration detection 4.2.2 Range-Doppler imaging LiDAR 4.2.3 Speckle imaging LiDAR 4.2.4 Aperture-synthesis–based LiDAR 4.3 Multiple-Input, Multiple-Output Active EO Sensing Appendix: MATLAB® program showing synthetic-aperture pupil planes and MTFs Problems and Solutions References 5 LiDAR Sources and Modulations 5.1 Laser Background Discussion 5.2 Laser Waveforms for LiDAR 5.2.1 Introduction 5.2.2 High time–bandwidth product waveforms 5.2.3 Radiofrequency modulation of a direct-detection LiDAR 5.2.4 Femtosecond-pulse-modulation LiDAR 5.2.5 Laser resonators 5.2.6 Three-level and four-level lasers 5.2.7 Laser-pumping considerations 5.2.8 Q-switched lasers for LiDAR 5.2.9 Mode-locked lasers for LiDAR 5.2.10 Laser seeding for LiDAR 5.2.11 Laser amplifier for LiDAR 5.3 Lasers Used in LiDAR 5.3.1 Diode lasers for LiDAR 5.4 Bulk Solid State Lasers for LiDAR 5.4.1 Fiber lasers for LiDAR 5.4.2 Nonlinear devices to change LiDAR wavelength 5.5 Fiber Format Problems and Solutions References 6 LiDAR Receivers 6.1 Introduction to LiDAR Receivers 6.2 LiDAR Signal-to-Noise Ratio 6.2.1 Noise probability density functions 6.2.2 Thermal noise 6.2.3 Shot noise 6.2.4 Background noise 6.2.5 Dark current, 1/f noise, and excess noise 6.3 Avalanche Photodiodes and Direct Detection 6.3.1 Linear-mode APD arrays for LiDAR 6.3.2 Direct-detection GMAPD LiDAR camera 6.4 Silicon Detectors 6.5 Heterodyne Detection 6.5.1 Temporal heterodyne detection 6.5.2 Heterodyne mixing efficiency 6.5.3 Quadrature detection 6.5.4 Carrier-to-noise ratio (CNR) for temporal heterodyne detection 6.5.5 Spatial heterodyne detection / digital holography 6.5.6 Receivers for coherent LiDARs 6.5.7 Geiger-mode APDs for coherent imaging 6.5.8 PIN diode or LMAPDs for coherent imaging 6.5.9 Sampling associated with temporal heterodyne sensing 6.6 Long–Frame-Time Framing Detectors for LiDAR 6.7 Ghost LiDARs 6.8 LiDAR Image Stabilization 6.9 Optical–Time-of-Flight Flash LiDAR 6.9.1 Summary of advantages and disadvantages of OTOF cameras Problems and Solutions References 7 LiDAR Beam Steering and Optics 7.1 Mechanical Beam-Steering Approaches for LiDAR 7.1.1 Gimbals 7.1.2 Fast-steering mirrors 7.1.3 Risley prisms and Risley gratings 7.1.4 Rotating polygonal mirrors 7.1.5 MEMS beam steering for LiDAR 7.1.6 Lenslet-based beam steering 7.2 Nonmechanical Beam-Steering Approaches for Steering LiDAR Optical Beams 7.2.1 OPD-based nonmechanical approaches 7.2.2 Chip-scale optical phased arrays 7.2.3 Electrowetting beam steering for LiDAR 7.2.4 Using electronically written lenslets for lenslet-based beam steering 7.2.5 Beam steering using EO effects 7.2.6 Phase-based nonmechanical beam steering 7.3 Some Optical Design Considerations for LiDAR 7.3.1 Geometrical optics 7.3.2 Adaptive optics systems 7.3.3 Adaptive optics elements Problems and Solutions Notes and References 8 LiDAR Processing 8.1 Introduction 8.2 Generating LiDAR Images/Information 8.2.1 Range measurement processing 8.2.2 Range resolution of LiDAR 8.2.3 Angle LiDAR processing 8.2.4 Gathering information from a temporally coherent LiDAR 8.2.5 General LiDAR processing 8.2.6 Target classification using LiDAR Problems and Solutions References 9 Figures of Merit, Testing, and Calibration for LiDAR 9.1 Introduction 9.2 LiDAR Characterization and Figures of Merit 9.2.1 Ideal point response main lobe width 9.2.2 Integrated sidelobe ratio 9.2.3 Peak sidelobe ratio 9.2.4 Spurious sidelobe ratio 9.2.5 Noise-equivalent vibration velocity 9.2.6 Ambiguity velocity 9.2.7 Unambiguous range 9.3 LiDAR Testing 9.3.1 Angle/angle/range resolution testing 9.3.2 Velocity measurement 9.3.3 Measuring range walk 9.4 LiDAR Calibration 9.4.1 Dark nonuniform correction 9.4.2 Results of correction Problems and Solutions References 10 LiDAR Performance Metrics 10.1 Image Quality Metrics 10.1.1 Object parameters 10.2 LiDAR Parameters 10.3 Image Parameters: National Imagery Interpretability Rating Scale (NIIRS) 10.4 3D Metrics for LiDAR Images 10.5 General Image Quality Equations 10.6 Quality Metrics Associated with Automatic Target Detection, Recognition, or Identification 10.7 Information Theory Related to Image Quality Metrics 10.8 Image Quality Metrics Based on Alternative Basis Sets 10.9 Eigenmodes 10.10 Compressive Sensing 10.10.1 Knowledge-enhanced compressive sensing 10.10.2 Scale-invariant feature transform 10.11 Machine Learning 10.12 Processing to Obtain Imagery 10.13 Range Resolutions in EO/IR Imagers 10.14 Current LiDAR Metric Standards 10.15 Conclusions Appendix: MATLAB code to Fourier transform an image Problems and Solutions Notes and References 11 Significant Applications of LiDAR 11.1 Auto LiDAR 11.1.1 Introduction 11.1.2 Resolution 11.1.3 Frame rate 11.1.4 Laser options 11.1.5 Eye safety 11.1.6 Unambiguous range 11.1.7 Required laser energy per pulse and repetition rate 11.1.8 Obscurants considered for auto LiDAR 11.1.9 Keeping the auto-LiDAR aperture clear 11.2 3D Mapping LiDAR 11.2.1 Introduction to 3D mapping LiDAR 11.2.2 3D mapping LiDAR design 11.3 Laser Vibrometers 11.3.1 Designing a laser vibrometer 11.4 Wind Sensing Problems and Solutions References Index

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