In recent years, the demand for 3D vision systems has increased in fields such as detection and recognition, motion
modelling, 3D environment reconstruction and tracking. This has motivated the development of range image
technology, especially Time-of-Flight (TOF) cameras, that provide direct measurement of distance between the
camera and the targeted surface. These devices have an advantage over traditional range data sensors due to
their capability to provide frame rate range data over a full image array. The quality of the measurement of
these sensors depends heavily on signal-to-noise (SNR) of the incoming signal and the subsequent processing
algorithms. In phase shift TOF cameras, phase shift sampling is used to measure amplitude, phase and the
offset (intensity) of the received signal. Each of these measurements has an associated statistical distribution
that affects the SNR of the TOF signal, limiting the reliability of 3D range data. It is crucial to understand the
statistical distributions of these three parameters for accurate distance measurement analysis especially in low
SNR scenarios. In this paper, we provide explicit noise models for the three parameters of amplitude, phase and
intensity. We use this analysis to provide an improved estimation of error in range measurement.
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