3D Time-of-flight distance measurement with custom - Universität ...
3D Time-of-flight distance measurement with custom - Universität ...
3D Time-of-flight distance measurement with custom - Universität ...
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DEMODULATION PIXELS IN CMOS/CCD 111<br />
sampling point, so that 50% <strong>of</strong> the received modulated light is evaluated and only<br />
50% is lost. This is an acceptable compromise when compared <strong>with</strong> the enormous<br />
improvement in fill factor (20% rather than 5%). This integration time <strong>of</strong> half the<br />
modulation period has no influence on the measured phase; it only attenuates the<br />
measured amplitude to 64% <strong>of</strong> the real amplitude, which is a consistent and<br />
predictable error (c.f. Section 2.2).<br />
opaque layer<br />
CCD gates<br />
oxide<br />
substrate<br />
potential<br />
intensity <strong>of</strong> incoming light<br />
sampling interval<br />
sampling interval<br />
sampling interval<br />
0V 10V 8V 0V 3.5V 0V 8V 10V<br />
integration<br />
direction<br />
(a)<br />
t<br />
dump<br />
direction<br />
dump<br />
diffusion<br />
potential<br />
i =<br />
s(<br />
t)<br />
⋅<br />
f(<br />
t<br />
+ τ)<br />
f(<br />
t<br />
+ τ)<br />
∫i = s(<br />
t)<br />
⋅ f(<br />
t + τ)<br />
= s(<br />
t)<br />
⊗ f(<br />
t)<br />
t=<br />
τ<br />
Q = ∫<br />
Figure 5.7 One-tap lock-in pixel: illustration <strong>of</strong> (a) sampling and (b) correlation<br />
process.<br />
The more serious drawback is the fact that the sampling points have to be acquired<br />
serially. This “serial tap-integration” reduces the application area <strong>of</strong> the pixel in <strong>3D</strong><strong>measurement</strong><br />
to scenes <strong>with</strong> relatively slow movements. The integrated sampling<br />
points Ai in Equation 2.17 contain both a fraction <strong>of</strong> integrated modulated light and<br />
a fraction <strong>of</strong> background light. If the sampling points are all taken at the same time<br />
(in parallel) they carry the same <strong>of</strong>fset, even if the scene changes (moves) during<br />
integration. With the subtraction <strong>of</strong> two sampling points the <strong>of</strong>fset disappears. The<br />
same is the case if the reflectance <strong>of</strong> an observed point changes during integration.<br />
However, if we acquire the sampling points serially and the reflectance or<br />
background intensity (<strong>of</strong>fset) changes from one sampling point to the other, the<br />
algorithm is no longer able to eliminate <strong>of</strong>fset and reflectance. Therefore, the 1-tap<br />
s(<br />
t)<br />
(b)<br />
s(<br />
t)