Multi-spectral laser detection and ranging for range profiling and surface characterization

Wallace, Andrew M.; Buller, Gerald S.; Sung, Raymond; Harkins, R.D.; McCarthy, Aongus; Hernandez-Marin, Sergio; Gibson, Gavin J.; Lamb, Robert A.

doi:10.1088/1464-4258/7/6/028

Cited by 14 publications

(13 citation statements)

References 9 publications

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“…Other more complex techniques involve Markov chain Monte Carlo methods 13,14 . Excellent application examples using these techniques for laser radar are found in the paper by Wallace et al 15 .…”

Section: Discussionmentioning

confidence: 99%

Range accuracy and resolution for laser radars

Steinvall

Chevalier

2005

Electro-Optical Remote Sensing

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Laser radars offer a potential for high range accuracy and range resolution due to short pulses and high bandwidth receivers. For angular non-resolved targets (1 D profiling) the analysis of the waveform offers the possibility of target recognition due to range profiling. For 2 D and 3 D imaging the angular and range resolution are the critical parameters for target recognition while in other applications such as in lidar mapping the range accuracy plays an important role for the performance. The development of the next generation laser radars including 3 D sensing focal plane arrays (FPAs) enable a full range and intensity image to be captured in one laser shot. Moreover, gated viewing systems also give a viable solution for providing 3 D target information.This paper uses simulation to illustrate the limits for accuracy and range resolution in waveform processing due to the laser pulse shape, detector noise, target shape and reflectivity as well as turbulence.

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Section: Discussionmentioning

confidence: 99%

Range accuracy and resolution for laser radars

Steinvall

Chevalier

2005

Electro-Optical Remote Sensing

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“…For that reason, two retroreflecting corner cubes were placed at a distance of 330 m from the TCSPC receiver described in [23] and the distance between these surfaces was varied from 1.7 cm to 71.2 cm.…”

Section: Algorithm Performance Measurementsmentioning

confidence: 99%

Bayesian Analysis of Lidar Signals with Multiple Returns

Hernandez-Marin

Wallace

Gibson

2007

IEEE Trans. Pattern Anal. Mach. Intell.

129

118

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Abstract-Time-Correlated Single Photon Counting and Burst Illumination Laser data can be used for range profiling and target classification. In general, the problem is to analyze the response from a histogram of either photon counts or integrated intensities to assess the number, positions, and amplitudes of the reflected returns from object surfaces. The goal of our work is a complete characterization of the 3D surfaces viewed by the laser imaging system. The authors present a unified theory of pixel processing that is applicable to both approaches based on a Bayesian framework, which allows for careful and thorough treatment of all types of uncertainties associated with the data. We use reversible jump Markov chain Monte Carlo (RJMCMC) techniques to evaluate the posterior distribution of the parameters and to explore spaces with different dimensionality. Further, we use a delayed rejection step to allow the generated Markov chain to mix better through the use of different proposal distributions. The approach is demonstrated on simulated and real data, showing that the return parameters can be estimated to a high degree of accuracy. We also show some practical examples from both near and far-range depth imaging.

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“…Recently methods to analyse multi-peak broad TCSPC TOF histograms have been suggested by Wallace et al [8]. Two different methods for interpreting experimental histograms were devised; a non-parametric peak finding ("bump hunting") and maximum likelihood (ML) methods In addition, a reversible jump Markov chain Monte Carlo (MCMC) method was used when the histogram was more complicated.…”

Section: 2mentioning

confidence: 99%

“…In addition to range-profiling the image capability of TCSPC has been demonstrated experimentally [7]. Recently a system based on TCSPC capable of registering reflected signals up to 13 km in daylight was presented [8,9,10]. By using integration times between 0.1 to 10 s, a distance resolution down to approximately 1 mm was obtained.…”

Section: Introductionmentioning

confidence: 99%

Time-of-flight range profiling using time-correlated single-photon counting

et al. 2007

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Optical range profiling with high resolution can be accomplished using single-photon counting time-of-flight techniques. Detection of optical surfaces with high resolution is of importance for several remote sensing applications. The use of laser pulses in the picosecond regime, single-photon detectors and acquisition electronics with high timing resolution provides the tools for improving the range accuracy. In this work a system based on time-of-flight range profiling using time-correlated single-photon counting techniques is described. The system is intended to be used for optical range profiling in field experiments. Experimental results from measurements on test targets are presented. Schemes for extraction of range information from the experimental temporal profile and results from performance modelling are briefly discussed.

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Multi-spectral laser detection and ranging for range profiling and surface characterization

Cited by 14 publications

References 9 publications

Range accuracy and resolution for laser radars

Range accuracy and resolution for laser radars

Bayesian Analysis of Lidar Signals with Multiple Returns

Time-of-flight range profiling using time-correlated single-photon counting

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