Improved phase detection algorithms for indirect time of flight range imaging cameras

Drayton, Benjamin M. M.; Carnegie, Dale A.; Dorrington, Adrian A.

doi:10.1109/rose.2012.6402622

Cited by 2 publications

(3 citation statements)

References 16 publications

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“…1 has two components, a sinusoidal component and an offset. However, it can be shown that the offset error is simply due to the selection of reference frame [19]. Changing the frame used as the reference frame changes the observed offset.…”

Section: Axial Motion Errormentioning

confidence: 99%

“…The problem of harmonics has been extensively examined in this field and can be adapted for our application. Furthermore the issue of axial motion error is analogous to a miscalibration of the phase step in Phase Shifting Interferometers [19], again it is assumed the amplitude is constant over the measurement time. We will therefore utilize Surrel's method of analysis using the phase algorithm's characteristic polynomial [22].…”

Section: Axial Motion Errormentioning

confidence: 99%

“…Knowing that ε = −vα/δ [19] the equivalent phase miscalibration error can be simulated. This provides equivalent results to those shown for traditional theory.…”

Section: Axial Motion Errormentioning

confidence: 99%

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Phase Algorithms for Reducing Axial Motion and Linearity Error in Indirect Time of Flight Cameras

2013

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Indirect time of flight cameras are increasingly being used in a variety of applications to provide real-time full field of view range measurements. Current generation cameras suffer from systematic linearity errors due to the influence of harmonics in the system and motion errors due to the requirement of taking multiple measurements. This paper demonstrates that replacing the standard phase detection algorithm with the windowed discrete Fourier transform can improve the root mean square (RMS) axial motion error with distance from 0.044 ± 0.002 m to 0.009 ± 0.004 m and the range from 0.112 ± 0.007 m to 0.03 ± 0.01 m for an object with a velocity of 2 m/s using a measurement time of 125 ms. This algorithm also improves the linearity of the camera by removing systematic errors due to harmonics, decreasing the RMS linearity error from 0.018 ± 0.002 m to 0.003 ± 0.001 m. This paper establishes the robustness of the windowed discrete Fourier transform, demonstrating that it effectively eliminates axial motion error over a variety of velocities and modulation frequencies. The potential for tailoring phase detection algorithms to specific applications is also demonstrated.

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Section: Axial Motion Errormentioning

confidence: 99%

Section: Axial Motion Errormentioning

confidence: 99%