Measuring equipment
Cezary Worek, Łukasz Krzak
EMC 2013
Agenda
1.
Basic EMC language.
2.
Noise.
3.
Nonlinearities in electronic circuits.
4.
Equipment for spectral analysis
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Traditional spectrum analyzer
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Vector signal analyzer
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Real-time spectrum analyzer
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EMI receiver
2
EMC language
3
Attenuation and gain.
Let’s consider a circuit with input voltage Vi and output voltage
Vo. To make it easier let’s assume that input impedance Ri is
equal to the output impedance Ro.
4
dB math
In case when two signals differ in orders of magnitude it is
desirable to express them using a logarithmic scale. Additionally
in gain (or attenuation) calculations we can replace
multiplication/division with addition/subtraction.
The unit of logarithmic scale are bel:
1 B = log10 (X1/X2)
or more often used decibel:
1 dB = 1/10 B
k = k1 x k2 [V]
k = k1 / k2 [V]
k = k1 + k2 [dB]
k = k1 - k2 [dB]
5
dB math
To be able to compute using decibel scale all source quantities
placed in numerator and denominator must be expressed in the
same units (in. ex. volts, ampers, watts).
So quantities expressed in bels or decibels are always ratios.
They are not interpreted as absolute signal values.
The following formulas can be used to calculate voltage and
current ratio – gain/attenuation:
ku = 20 logV1/V2
ki = 20 logI1/I2
6
dB math
Power ratio can be expressed as:
kp = 10 logP2/P1
From this we can derive:
kp = (Vo2/Ro) / (Vi2/Ri) = 10 log (Vo2/Vi2 x Ri/Ro) =
= 20 log Vo/Vi + 10 logRi/Ro
When Ri = Ro, logarithm of 1 is 0 and the ratios of voltage, current
and power expressed in dB are the same.
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dB units
Normally the values in dB express only ratio, not absolute value. In practice it is often
desirable to be able to express also absolute signal values using logarithmic scale.
In such notation, dB + additional unit expresses absolute value. Following standard
units were defined:
Absolute voltage levels:
20 lg U/1V in dBV
20 lg U/1mV in dBmV
20 lg U/1uV in dBuV
Absolute power levels:
10 lg P/1W w dBW
10 lg P/1mW w dBmW = dBm
1mW = 0dBm is equal to 224mVRMS on a 50Ω load.
8
Noise
9
Thermal noise
Thermal noise is unavoidable, and generated by the random thermal motion of
charge carriers (usually electrons), inside an electrical conductor, which happens
regardless of any applied voltage.
Thermal noise is approximately white, meaning that its power spectral density is
nearly equal throughout the frequency spectrum. The amplitude of the signal has
very nearly a Gaussian probability density function
Noise voltage:
un  4kTRf
Noise power:
Pn  kTf
R
Where: k = 1.3806488×10−23 J/K (Boltzmann constant)
T – absolute temperature in K
Δf – bandwidth
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Thermal noise example
T = 290 K (17 Celsius)
R = 50 Ohm
For unitary bandwidth Δf = 1Hz:
Un = 0.89 nV
Pn = 4×10-21 W = -174 dBm = -204 dBW
For narrow channel Δf = 10kHz:
Un = 89 nV
Pn = 4×10-17 W = -134 dBm = -164 dBW
For a single WiFi channel Δf = 22MHz:
Un = 4.20 uV
Pn = 8.8×10-14 W = -100 dBm = -130 dBW
11
Shot noise.
Shot noise is a type of electronic noise which originates from the discrete nature of
electric charge (e=1,6·10-19). The term also applies to photon counting in optical
devices, where shot noise is associated with the particle nature of light.
Shot noise becomes visible in a PN junction (diode) when the charge carriers cross
the energy band gap.
I s  2eI  f  
DC current
noise current
If U < 0 then
where
I  I diff  I drift
I  I drift
and
 1
I  I diff
and
 1
(drift current dominates)
If U > 0 then
(diffusion current dominates)
If U = 0 then
It is worth to note that:
is (t )  0
but
I drift  I diff
is (t )
2
2
 Is
For 1A, Δf=1Hz, the shot noise current is ≈ 0,565·10-19 A.
12
Nonlinearities in electronic circuits
13
Nonlinearities
The output signal of a two-port network can be given as:
Where: k0 is the mean value (DC)
k1 is signal gain
k2 is the second derrivative and so on..
Even if the input signal is single harmonic:
The output will have multiple harmonics.
14
Nonlinearities
15
Compression and detection
16
Intermodulation
Now suppose that the input is a two-harmonic signal:
Then on the output we get:
Using simple trigonometric transformations we get a lot of additional products
(spectral components) being caused by:
• mixing of signals
• multiplying the frequency
• detection (mean - „DC” value)
• compression
17
Third order intercept point (IP3 or TOI)
Since the 3rd order products increase 3 times faster that the fundamental (linear)
product, we can ask at what input level both of these products will be equal. This
artificial point is called the input third order intercept point (IIP3) and is a commonly
used measure of input nonlinearity.
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Equipment for spectral analysis
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Spectrum analyzer (SA)
Spectrum analyzers are electronic measurment devices that show power magnitude
of an input signal versus frequency. Compared to oscilloscopes, spectrum analyzers
usually have more dynamic range and much better sensitivity, which allows to take a
more in-depth look at particular signals, showing details that are not visible on a
standard scope.
Typically, spectrum analyzeres are used for:
• characterization of RF transceivers (center frequency, modulation parameters)
• observing EM environment (radio signals)
• measuring signal bandwidth and distortion
• etc.
Many spectrum analyzers are equipped with
a tracking generator that allows to measure
spectral transmitance of a two-port network
(in ex. filter or amplifier)
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What can we measure with a spectrum analyzer?
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Spectral power density
Signal power over some bandwidth
Spectrum occupation
Scalar and vector transmittance
Scalar and vector matching
Signals that are hidden in the spectrum (in ex. Masked by higher amplitude
signals)
Signals masked by noise
Frequency drift
Phase noise
Modulation characteristics
Frequency hopping signals
Unwanted transmissions
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How does a „standard” spectrum analyzer work?
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Input attenuator.
In our HAMEG HM5014-2:
Input attenuator range: 0..40dB in 10dB increments
Max. Input Level (continuous):
• +20dBm (0,1W) when using 40dB attenuation
• +10dBm (10mW) when using 0dB attenuation
Max. DC Voltage: +/- 25V
Measurement range: +10dBm .. -100dBm
23
Input filter.
In our HAMEG HM5014-2:
Input filter bandwidth: 150kHz.. 1050MHz
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Mixer + local oscillator
f IF  f LO  f IN
But since always; f LO  f IN
The actual equation becomes: f IF  f LO  f IN
SA tuning equation:
25
Mixer + local oscillator
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Real spectrum analyzers use multiple mixers
Most spectrum analyzers on the market use two to four mixers that shift the signal
into different frequency bands. The first frequency shift is always up, to a band above
the maximum input frequency.
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IF gain
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IF filter – resolution bandwidth
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Logarithmic amplifier
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Detector.
Typical envelope detector
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Detector types.
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Sample
Positive peak (also simply called peak)
Negative peak
Normal
Average
Quasi-peak
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Video filter
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Preamplifier.
Some spectrum analyzers may be equipped with a built-in preamplifier that can
further improve input sensitivity. Such preamplifier (in example with gain of +20dB) is
switched on depending on the signal magnitude.
This feature is important for example in radiated emission measurements (when
signals are generally low)
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Vector signal analyzer (VSA)
The vector signal analyzer digitizes the analog input signal and uses DSP technology
to process and provide data outputs; the FFT algorithm produces frequency domain
results, the demodulator algorithms produce modulation and code domain results.
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SA vs VSA.
A traditional swept-spectrum analyzer sweeps a narrowband filter across a range of
frequencies, sequentially measuring one frequency at a time. Unfortunately,
sweeping the input works well for stable or repetitive signals, but will not accurately
represent signals that change during the sweep. Also, this technique only provides
scalar (magnitude only) information, though some other signal characteristics can be
derived by further analysis of spectrum measurements.
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SA vs VSA.
The VSA measurement process simulates a parallel bank of filters and overcomes
swept limitations by taking a “snapshot,” or time-record, of the signal; then
processing all frequencies simultaneously. For example, if the input is a transient
signal, the entire signal event is captured (meaning all aspects of the signal at that
moment in time are digitized and captured); then used by the FFT to compute the
“instantaneous” complex spectra versus frequency.
37
SA vs VSA.
DSP yields additional benefits - it provides time, frequency, modulation, and code
domain measurement analysis in one instrument. The analog demodulator produces
AM, FM and PM demodulation results, allowing you to view amplitude, frequency,
and phase profiles versus time. The digital demodulator performs a broad range of
measurements on many digital communications standards (such as W-CDMA, GSM,
and more) and produces many useful measurement displays and signal-quality data.
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Dead time.
Both the traditional SA and VSA suffer from the „dead time” problem. In case of a SA
the assumption is that during the sweep (or several sweeps) the signal does not
change much. If there is a rapid change in the signal, it is statistically probable that
this change will be missed. As shown in figure above, the sweep is looking at
frequency segment Fa while a momentary spectral event occurs at Fb (diagram on
left). By the time the sweep arrives at segment Fb, the event has vanished and does
not get detected (diagram on right). The SA does not provide a way to trigger on this
transient signal, nor can it store a comprehensive record of signal behavior over time.
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Dead time.
The VSA is optimized for modulation measurements. Like the Real-Time Spectrum
Analyzer described in the next section, a VSA digitizes all of the RF energy within the
passband of the instrument in order to extract the magnitude and phase information
required to measure digital modulation. However, most (but not all) VSAs are
designed to take snapshots of the input signal at arbitrary points in time, which
makes it difficult or impossible to store a long record of successive acquisitions for a
cumulative history of how a signal behaves over time. Like a swept SA, the triggering
capabilities are typically limited to an IF level trigger and an external trigger.
The Real-Time Spectrum Analyzer is designed to address the measurement
challenges associated with transient and dynamic RF signals as described in the
previous section. The fundamental concept of real-time spectrum analysis is the
ability to trigger on an RF signal, seamlessly capture it into memory, and analyze it in
multiple domains. This makes it possible to reliably detect and characterize RF signals
that change over time.
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Dead time – RSA solution.
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RSA applications.
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Transient and dynamic signal capture and analysis
Capturing burst transmissions, glitches, switching transients
Characterizing PLL settling times, frequency drift, microphonics
Detecting intermittent interference, noise analysis
Capturing spread-spectrum and frequency-hopping signals
Monitoring spectrum usage, detecting rogue transmissions
Compliance testing, EMI diagnostics
Analog and digital modulation analysis
Characterizing time-variant modulation schemes
Troubleshooting complex wireless standards using domain correlation
Performing modulation quality diagnostics
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Time-frequency domain.
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RSA advantages.
Conventional SA
RTSA
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RSA advantages.
Conventional SA
RTSA
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RSA advantages.
Conventional SA
RTSA
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RSA advantages.
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RSA advantages.
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SA vs VSA vs RTSA
SA
VSA
Modern FFT
RTSA
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SA vs VSA vs RTSA
Traditional Sweeping Analyzer
 High RF dynamic range
 Low phase noise
Real-time SA
 Sweeping with mapping
 Complex trigger system
 Fast signal anaysis (wide
windows of analysis)
Vector SA
 Correlated time / amplitude /
 Constelation plot
phase /frequency analysis
 Symbol analysis
 Advanced impulse analysis
 Long acquisition time
 Matching analysis
 High magnitude and phase
accuracy
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EMI receiver.
„For many applications, the spectrum analyser is perfectly adequate, provided that it
has ‘real’ QP and average detectors and an adequate dynamic range. However, there
are circumstances when a spectrum analyser will give false results.”
„A check with the EMC ‘bible’ (CISPR16) will show that all radiated and conducted
emission levels should be measured with a ‘measuring receiver’. Most of us will be
using a ‘spectrum analyser’ or EMC analyser, not a measuring receiver! The essential
difference between an analyser and a receiver is the ‘pre-selector’. This
unfortunately tends to be an expensive item, judging by the price differential
between analysers and recievers. However, if the bible thinks it is important, perhaps
we ought to at least know what it is and why it is apparently necessary.”
Technical Notes from Laplace Instruments Ltd
„Pre selectors... what, why and when?”
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EMI receiver.
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EMI receiver.
The EMI receiver differs from a traditional spectrum analyzer because it has
a pre-selector.
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EMI receiver.
The essential features of a spectrum analysis are depending on the MIXER which
mixes the incoming signal with a pure frequency from a local oscillator. The resulting
mixer output includes sum and difference frequencies which are filtered to produce a
fixed frequency I.F. signal which is detected and fed to the vertical scale on the
display.
Note that the incoming signal is effectively fed directly to the mixer, so it has to cope
with all frequencies and has a broadband characteristic. Mixers have only a certain
amount of dynamic range.
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EMI receiver.
CISPR 16 conducted emissions measurements from 150 kHz to 30 MHz:
Reduce RF Overloading and Its Effects; With the use of a preselector, the bandwidth
of the energy presented to the first mixer is reduced, thereby reducing mixer
overload and measurement errors. Improve Radiated Emissions Measurement
Sensitivity
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EMI receiver.
Typical equipment configuration.
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EMI receiver.
The effect of the pre-selector is to allow only a narrow band of frequencies through
to the mixer. This band includes the frequency currently being swept. As the sweep
frequency increases and reaches the end of one band, the pre-selector switches over
to the next highest.
The diagram shows the effect of the preselector as the analyser sweeps through
band 6. Only band 6 signals are visible to
the mixer, all other frequencies having
been attenuated by the pre-selector filter.
In particular, the high energy signals are
removed and the sensitivity of the
‘analyser’ can be increased by reducing
the attenuators so that the low level EUT
signals can be properly measured without
suffering compression.
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