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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OPTICAL TOF RANGE MEASUREMENT 37<br />
and algorithms in order to understand clearly and easily what happens to the phase<br />
spectrum. In a next step we will transfer these results to a square wave. And lastly<br />
we will simulate aliasing effects on several other waveforms, presuming DFT<br />
detection <strong>with</strong> four sampling points.<br />
An important boundary condition is the chosen integration interval for the sampling<br />
point acquisition. As already discussed this is chosen to be half the modulation<br />
period ∆t=T/2 in the following calculations. From Figure 2.8 we can conclude that,<br />
for ∆t=T/2, all even harmonics <strong>of</strong> the basic frequency, namely 2f, 4f, 6f, … will be<br />
suppressed and do not contribute to the demodulation result. This is because these<br />
harmonics are eliminated by a zero crossing <strong>of</strong> the sinc-function. This simple<br />
example shows the importance <strong>of</strong> the choice <strong>of</strong> ∆t for aliasing effects.<br />
Aliasing phase error for 3f-harmonic using 4-tap DFT-detection.<br />
In order to simplify explanations we use the expression “tap” for “sampling point”<br />
from now on. We consider the input signal s(t) having a harmonic <strong>of</strong> triple base<br />
frequency and amplitude “1”.<br />
( ω t − ϕ ) + cos(<br />
3ω<br />
t − 3 )<br />
s( t)<br />
ϕ<br />
= cos 0 0<br />
0 0<br />
Equation 2.22<br />
The phase delay ϕ0 is caused by the <strong>distance</strong> dependent time delay in our TOF<br />
application. This time delay causes a phase delay <strong>of</strong> 3ϕ0 in the 3f-harmonic<br />
component.<br />
Transformed into the Fourier domain we obtain the spectrum S(f):<br />
S(<br />
f)<br />
=<br />
1<br />
2<br />
{<br />
δ<br />
+ δ<br />
−jϕ<br />
( ω − ω ) 0<br />
0 ⋅ e<br />
jϕ<br />
+ δ(<br />
ω + ω ) 0<br />
0 ⋅ e<br />
( ω − 3ω<br />
−j3ϕ<br />
) ⋅ e 0 + δ(<br />
ω + 3ω<br />
j3ϕ<br />
) ⋅ e 0 }<br />
0<br />
0<br />
Equation 2.23<br />
Now we consider the integration <strong>of</strong> the taps, i.e. convolution <strong>of</strong> s(t) <strong>with</strong> rect(t/∆t)<br />
and multiplication <strong>of</strong> S(f) <strong>with</strong> sinc(2π⋅f⋅∆t/2)=sinc(π⋅f⋅T/2) resulting in:<br />
Sint(<br />
f)<br />
=<br />
1<br />
2<br />
2<br />
<strong>with</strong> a =<br />
π<br />
{<br />
a ⋅<br />
+ b ⋅<br />
and<br />
− jϕ<br />
( δ(<br />
ω − ω ) e 0<br />
0 ⋅<br />
jϕ<br />
+ δ(<br />
ω + ω ) e 0<br />
0 ⋅ )<br />
− j3ϕ<br />
( δ(<br />
ω − 3ω<br />
) e 0<br />
0 ⋅<br />
j3ϕ<br />
+ δ(<br />
ω + 3ω<br />
) e 0<br />
0 ⋅ )}<br />
2 a<br />
b = − = −<br />
3π<br />
3<br />
Equation 2.24<br />
The coefficients a and b are obtained by evaluation <strong>of</strong> sinc(π⋅f⋅T/2) at f=1/T and<br />
f=3/T, respectively. By substituting b <strong>with</strong> a and considering -1 = e jπ = e -jπ we only