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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

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