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Understanding and Ameliorating Mixed Pixels and Multipath Interference in AMCW Lidar

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TOF Range-Imaging Cameras

Abstract

Amplitude modulated continuous wave (AMCW) lidar systems suffer from significant systematic errors due to mixed pixels and multipath interference. Commercial systems can achieve centimetre precision, however accuracy is typically an order of magnitude worse limiting practical use of these devices. In this chapter the authors address AMCW measurement formation and the causes of mixed pixels and multipath interference. A comprehensive review of the literature is given, from the first reports of mixed pixels in point-scanning AMCW systems, through to the gamut of research over the past two decades into mixed pixels and multipath interference. An overview of a variety of detection and mitigation techniques, including deconvolution based intra-camera scattering reduction, modelling of intra-scene scattering, correlation waveform deconvolution techniques/multifrequency sampling and standard removal approaches, all of which can be applied to range-data from standard commercial cameras is presented. The chapter concludes with comments on future work for better detection and correction of systematic errors in full-field AMCW lidar.

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Notes

  1. 1.

    Although primarily intended to mitigate aliasing of correlation waveform harmonics, these linearity calibrations also allow correction for systematic errors due to other effects like crosstalk.

  2. 2.

    In other words, a pulsed system which only returns the range to the closest backscattered return.

  3. 3.

    Strictly, the scattering PSF is complex domain, and the phase of the complex number is a linear function of range. It is important to distinguish the scattering PSF, which is independent of range, from the defocus PSF, which is not.

  4. 4.

    For example, from a Bayesian perspective Tikhonov regularisation corresponds to the assumption of a Gaussian distribution of intensity values.

  5. 5.

    This manifests as aliasing if only a small number of samples are taken of the correlation waveform, hence the importance of harmonic cancellation techniques.

  6. 6.

    For example, if using frequencies of 30 and 20 MHz, the component returns, \(\eta _0\) and \(\eta _1\), would be notated as if captured at a frequency of 10 MHz. This means that there is no cyclic ambiguity, and enables the representation in Eqs. 33 and 34.

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Authors and Affiliations

  1. School of Engineering, University of Waikato, Hamilton, New Zealand

    John P. Godbaz, Adrian A. Dorrington & Michael J. Cree

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  1. John P. Godbaz
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  2. Adrian A. Dorrington
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  3. Michael J. Cree
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Correspondence to John P. Godbaz .

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Editors and Affiliations

  1. , 3D Optical Metrology (3DOM), Fondazione Bruno Kessler, Trento, Italy

    Fabio Remondino

  2. , Smart Optical Sensors and Interfaces, Fondazione Bruno Kessler, Trento, Italy

    David Stoppa

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Godbaz, J.P., Dorrington, A.A., Cree, M.J. (2013). Understanding and Ameliorating Mixed Pixels and Multipath Interference in AMCW Lidar. In: Remondino, F., Stoppa, D. (eds) TOF Range-Imaging Cameras. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27523-4_5

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