A phase detector characteristic is a function of phase difference describing the output of the phase detector.
For the analysis of Phase detector it is usually considered the modelsof PD in signal (time) domain and phase-frequency domain.[1] In this case for constructing of an adequate nonlinear mathematical model of PD in phase-frequency domain it is necessary to find the characteristic of phase detector.The inputs of PD are high-frequency signals and the output contains a low-frequency error correction signal, corresponding to a phase difference of input signals. For the suppression of high-frequency component of the output of PD (if such component exists) a low-pass filter is applied. Thecharacteristic of PD is the dependence of the signal at theoutput of PD (in the phase-frequency domain) on the difference of phases at the input of PD.
This characteristic of PD depends on the realization of PD and the types of waveforms of signals. Consideration of PD characteristic allows to apply averaging methods for high frequency oscillations and to pass from analysis and simulation of non autonomous models of phase synchronization systems in time domain to analysis and simulation of autonomous dynamical models in phase-frequency domain .[2]
Consider a classical phase detector implemented with analog multiplier and low-pass filter.
Here
f1(\theta1(t))
f2(\theta2(t))
f1(\theta)
f2(\theta)
\theta1,2(t)
g(t)
f1,2(\theta)
\theta1,2(t)
\phi(\theta)
g(t)=
t | |
\int\limits | |
0 |
f1(\theta1(t))f2(\theta2(t))dt
G(t)=
t | |
\int\limits | |
0 |
\varphi(\theta1(t)-\theta2(t))dt
g(t)-G(t) ≈ 0
Consider a simple case of harmonic waveforms
f1(\theta)=\sin(\theta),
f2(\theta)=\cos(\theta)
\sin(\theta1(t))\cos(\theta2(t))=
1 | |
2 |
\sin(\theta1(t)+\theta2(t))+
1 | |
2 |
\sin(\theta1(t)-\theta2(t))
\sin(\theta1(t)+\theta2(t))
\sin(\theta1(t)-\theta2(t))
Consequently, the PD characteristic in the case of sinusoidal waveforms is
\varphi(\theta)=
1 | |
2 |
\sin(\theta).
Consider high-frequency square-wave signals
f1(t)=sgn(\sin(\theta1(t)))
f2(t)=sgn(\cos(\theta2(t)))
\varphi(\theta)=\begin{cases} 1+
2\theta | |
\pi |
,&if\theta\in[-\pi,0],\\ 1-
2\theta | |
\pi |
,&if\theta\in[0,\pi].\\ \end{cases}
Consider general case of piecewise-differentiable waveforms
f1(\theta)
f2(\theta)
This class of functions can be expanded in Fourier series.Denote by
p | ||||
a | ||||
|
\pi | |
\int\limits | |
-\pi |
fp(x)\sin(ix)dx,
p | ||||
b | ||||
|
\pi | |
\int\limits | |
-\pi |
fp(x)\cos(ix)dx,
p | ||||
c | ||||
|
\pi | |
\int\limits | |
-\pi |
fp(x)dx,p=1,2
f1(\theta)
f2(\theta)
\varphi(\theta)=c1c2+
1 | |
2 |
infty | |
\sum\limits | |
l=1 |
2 | |
((a | |
l |
+
2 | |
b | |
l)\cos(l\theta) |
+
2 | |
(a | |
l |
-
2 | |
b | |
l)\sin(l\theta)). |
Obviously, the PD characteristic
\varphi(\theta)
R
Modeling method based on this result is described in [6]