SCALAR NETWORK ANALYSIS:AN ATTRACTIVE AND COSl-EFFECTIVE

TECHNIQUE FOR TESTINGMICROWAVE COMPONENTS

Hugo VitianNetwork Measurements Division

1400 Fountain Grove ParkwaySanta Rosa, CA 95401

RF ~ MicrowaveMeasurementSymposiumandExhibition

Flio- HEWLETT~~ PACKARD

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Scalar Network Analysis: an Attractive andCost-Effective Technique for Testing MicrowaveComponents

ABSTRACT

Scalar network characterization is an economic alternativeto vector network analysis; in particular, in a productiveenvironment where ease-of-use, throughput and low cost arekey considerations.

However, scalar measurements are not restricted to frequencyresponse measurements on linear networks. Scalar networkanalyzers are very powerful analysis tools to characterizeamplifiers, mixers, modulators, and other components as afunction of signal level or control parameter, as well asfor cable testing in frequency- and distance-domains.

This presentation describes the fundamental measurementconcepts and discusses some specific examples.

Author: Hugo Vifian, Engineering Section Manager foreconomy vector network analyzers, HP Network MeasurementsDivision, Santa Rosa, CA. Diplom-Ingenieur and PhD fromSwiss Federal Institute of Technology, (ETH). With HP since1969, projects include HP 8755 frequency response test set,HP 8505 RF vector network analyzer, HP 8756 and 8757 scalarnetwork analyzers.

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INTRODUCTION TO SCALARNETWORK MEASUREMENTS

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INTRODUCTION TO SCALARNETWORK MEASUREMENTS

Introduction: Even though scalarmicrowave measurements have beenmade ever since high frequencieswere discovered, they were notreally addressed, as such, butrather called power measurements orVSWR measurements, etc. It was notuntil modern network analysis withvector error correction was intro­duced that the rather obvious termmagnitude or scalar measurementsbecame more popular.

The objectives of this presentationare:

Discuss practical scalar measure­ment applications.

Introduce a variety of networkcharacterization techniques in themicrowave frequency range.

OBJECTIVES• Introduce Scalar Measurement

Concepts

• Explain Network CharacterizationTechnique in the MicrowaveFrequency Range

• Discuss Practical MeasurementApplications

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To explainScalar andconcepts.

the difference betweenVector Network Analyzer

SCALARMEASUREMENT CONCEPTS

• Scalar and Vector Network AnalyzerComparison

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1. SCALAR MEASUREMENT CONCEPTS

The fundamental difference betweenVector and Scalar Network Analyzersstems from different receiver con­cepts applied. All the other sys­tems characteristics are a director indirect result of this.

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1.1 SCALAR AND VECTOR NETWORKANALYZER COMPARISON

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SCALAR AND VECTOR NETWORKANALYZER COMPARISON

Receiver • Homodyne • HeterodyneConcept Mostly Mostly

Single Converter Multi-Converter(MW-DC) (MW-IF1-IF2-DC)

Front End • Diode Detector • FundamentalFrequency or orConverter Thermo Couple Harmonic Mixer

The Scalar Analyzer Receiver mea­sures the magni tude of the micro­wave test signal to be measured byconverting it into a low frequencyAC or DC signal by means of a ther­mo electrical effect or a diodehomodyne process. (1)

Most Vector Network Analyzers, onthe other hand, are heterodynereceivers with multiple frequencyconverters based on fundamental orharmonic mixing with a local oscil­lator signal. (2)

SCALAR VECTOR

VECTOR NETWORK ANALYZER BLOCK DIAGRAMS

SignalProcessingandDisplay

Test Set and Receiverr-------------,I Front End

T

Sourcer --.,I

: rv}-!----!..---l+!

I

:AIIIIIIIL __.J

SweptSource

Subsequent filtering allows reduc­ing the processing bandwidth andtherefore improving the signal-to­noise ratio which ultimately leadsto improved sensitivity and dynamicrange. Furthermore, the narrowbandreceiver characteristic suppressesharmonic and spurious signals atother frequencies.

The Vector Analyzer then measuresthe down converted microwave signalcharacteristics in terms of ampli­tude and phase at a low intermedi­ate frequency (IF).

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SCALAR NETWORK ANALYZER BLOCK DIAGRAM

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L ~

BroadbandHomodyneReceiver

Source Test Set and Receiver

r - -, r - -0;;';. ;'t.:-o,- - - - - - --,I 0 I Front End

I rv~-!-_----;+f ¥ ~I----+::J----~I I II L __ :J Signa'':A

L---------Kl-----+f ~;::,c.ss'ngDisplay

IIIIIIL __ .J

SweptSource

In contrast, Scalar Network An­alyzers with diode detectors asfrequency (down) converters areinherently broadband receivers. (4)

This gives them the capability tomeasure any signal in the entirefrequency band instantaneously. Afeature which is important forcharacterizing frequency translat­ing components (mixers), or whenhigh frequency agility is required.The trade offs are: a) less sen­sitivity mainly because of thebroadband noise and lower conver­sion efficiency of the diode con­verter and b) limited rejection ofundesirable signal components. (5)

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-10 dBm

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A simple way to model such a con­figuration is a mixer multipliercircuit with both RF and La inputsconnected together. At high RFpower levels, the signal at the Lainput is sufficient to convert theRF signal proportionally (with anominal conversion loss) to theoutput of the mixer.This operating area is calledlinear (conversion) for the diodedetector and an incremental changeat the input generates a propor­tional change in (detected) outputsignal.As the RF signal is reduced, the Lacomponent in the model drops andthe conversion efficiency is re­duced until the RF and La only con­tribute in a mUltiplicative way tothe output signal. Therefore atlow signal levels, an incrementalRF input signal drop translatesinto twice the drop of detectedsignal at the output. This diodeoperating area is called square law(conversion) since the detectedsignal is proportional to the prod­uct of RF and La which is RF­squared.When used as a Scalar Analyzerfront end, the diode square lawcharacteristic is extended by ap­propriate signal processing overthe entire operating range (dynamicrange) in order to maintain a cali­brated display.

VECTOR• Narrow Band• High

Selectivity

• High Sensitivity(~-100 dBm,Wide DynamicRange)

• SynchronouslyTuned LocalOscillator

• Higher Cost& Performance

SCALAR

• Self-ConvolvingMixer WithoutLocal Oscillator

• Lower Cost& Performance

DIODE DETECTOR AS FREQUENCY CONVERTER

Log Vo

Voltage !OutputPro ortionalto Power

SCALAR AND VECTOR NETWORKANALYZER COMPARISON

to Power !IL-+--+--+-+--+-+--+--+ Log

PIN = V,ZZo

Basic • Broad BandCharacteristics • Very Frequency

Agile

• LowerSensitivity(~-60 dBm)

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SCALAR AND VECTOR NETWORKANALYZER COMPARISON

SCALAR VECTOR

Having the signal vectors availablein complex form (amplitude andphase) allows the applicationsophisticated error correctiontechniques which dramatically re­duces measurement ambiguities. (3)

FundamentalMeasurements

Accuracy

• SignalMagnitudeorMagnitudeSquared(Power)

• Scalar ErrorCorrectionOnly

• SignalAmplitudeandPhase

• ElaborateVector ErrorCorrection

However, the improved performanceof a Vector Network Analyzer doesnot come for free and the hardwarecost of the heterodyne structurewith the synchronously tuned localoscillator and the additional pro­cessing capability adds substan­tially to the cost of this measure­ment system.

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1.2 FUNDAMENTAL SCALARMEASUREMENTS

Let's quickly review the two mostcommon scalar measurement concepts:1. Transmission2. Reflectionas a function of frequency. (6)(7)

FUNDAMENTAL SCALAR MEASUREMENTSTransmission (vs. Frequency)

TDUT

A

TRANSMISSION: 2647

The swept source provides a testsignal over the frequency range ofinterest which is applied to thedevice under test (DUT) and thetransmitted signal (T) is measuredby the Scalar Analyzer. Since weare usually interested in Transmis­sion Gain or Loss, the incedentsignal (I) is measured and comparedwith the transmitted signal and thesignal ratio is computed as shownin the graph below.

Gain/Loss ; TransmittedIncident

Frequency

As an example, the transfer func­tion or gain of a band-pass filteris displayed as a function offrequency.

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REFLECTION:

Reflection Measurements (vs. Frequency)

OUT

DevicePort

ITest

Directional PortDevice I

Slotted Line IncidentCoupler ~~~=":""--I'"Bridge

Source

In a reflection measurement, theincident and reflected signal areseparated by a directional device(bridge coupler, etc.) and measuredeither separately, or as a super­position in form of a standing wavepattern (slotted line).

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r'M (~, V5WR, RL, 5,,)

Frequency

The reflection coefficient, gammais then computed by either formingthe ratio of reflected (R) overincident (I) signal or by convert­ing the standing wave ratio asshown later.

r, * r'MMeasurement Errors are a Function of:Directivity (D), Test Port Match (rTP) andDevice Match (r,)

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ACCURACY CONSIDERATIONS:

Unfortunately, a perfect separationof incident and reflected signal isnot possible. A part of the inci­dent signal, attenuated by the di­rectivity (D) of the directionaldevice will be present also. Fur­thermore, since the directionaldevice does not have a perfect portmatch, some of the reflected signal(gamma-L) gets re-reflected(gamma-TP). Mainly, these two er­ror terms cause the measuredreflection coefficient (gamma-LM)of the device under test to be dif­ferent than the actual term(gamma-L).

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0::o0::

t5 0

L:

~ +2 h..e-~·-~-~~H

~ +3L: +4

+50

INF-5

rTP

-4

III -3"U

- 2 h,,',5~~~i-------:7"

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The chart and the table show how wecan estimate the measurement ambi­guity caused by the directivity (D)and the test port match (gamma-TP)as a function of the value ofreflection coefficient to be mea­sured (gamma-L).

For high returnloss measurements(gamma-L >20dB), the directivity(D) dominates the ambiguityand for lower returnloss(gamma-L (10dB),the test port matchbecomes the major contributor.

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*

*

~2.0

rTP

VSWR

30

40

40

DdB

40

4 dB

10 dB

30 dB

20 dB

Examples: ErrorAmbiguity

30 +3.5 dB-2.5

20 + 1.0 dB- .9+ 1.3 dB-1.2

4 +2.5 dB-2.0

CD 4 dB 40 ~1.1 4 ±.4 dB

For High (~20 dB) Return Loss MeasurementsDirectivity Dominates, for Low (~10 dB) R.L.the Test Port Match Dominates

CDCDCD

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2. SCALAR NETWORKCHARACTERIZATION TECHNIQUES

2.1 OVERVIEW

A Scalar Analyzer is really ageneralized stimulus response testset capable of doing a wide varietyof network characterization tasks.

Frequency response measurements areprobably the most popular forlinear networks.

Other networks may exhibit signallevel dependent parameters likeamplifiers.

Another group of stimulus responsemeasurements allows us to charac­terize networks in a time/distanceor impedance domain.

ADVANCEDNETWORK CHARACTERIZATIONTECHNIQUES: AN OVERVIEW

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MEASUREMENT DOMAINS• Frequency Response (or Versus

Frequency) Measurements

• Network CharacterizationVersus Signal Level

• Frequency, Time and ImpedanceDomain Characterization

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STIMULUS -+ RESPONSECONCEPT

8

Stimulus

Response(Reflection)

Deviceor

NetworkUnderTest

Response(Transmission)

~

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FREQUENCY RESPONSE OF LINEAR NETWORKS

2.2 FREQUENCY RESPONSE OF LINEARNETWORKS

Stimulus(Source)

OUT

TransmittedSignal

We already covered the most impor­tant scalar measurements (transmis­sion and reflection) of this classof networks.

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Example: Filter

Frequency Response is Independentof Signal Level (Linear)

An additional selection of relatedmeasurements is listed below.

Transmission Reflection

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BASIC FREQUENCYRESPONSE MEASUREMENTSTRANSMISSION

• Gain/Loss

• Bandwidth

• Attenuation

• Coupling

• Directivity

• Etc.2623

REFLECTION

• Return Loss

• Impedance

• VSWR

• ReflectionCoefficient

• Etc.

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These parameters are either direct­ly derived from the basic transmis­sion or reflection measurementslike bandwidth and directivity orare computed from the fundamentalmeasurement like VSWR fromreturnloss either internally to theAnalyzer, or externally with acontroller/computer.

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CHARACTERIZATIONOF PSEUDO-LINEAR NETWORKS

2.3 CHARACTERIZATION OF PSEUDOLINEAR NETWORKS

For example, an amplifier is a net­work where some of the keyparameters may depend on the signallevel. In that case, the frequencyresponse has to be measured forvarious power levels to fullycharacterize its behavior.

Amplifiers

A

InputSignal

l>Example: Amplifier

OutputSignal

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Furthermore, it is often importantto meC\sure the gain as a functionof the input or output signal toestablish the maximum power gain orthe compression points.

Gain

Frequency Response Depends onSignal Level (Non-Linear)

Gain

~-20dBm

v:::-

Frequency..

Signal Level

..-2625

Here is a set of additional mea­surements that might be required tobetter characterize this class ofnetworks.

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ADDITIONAL FREQUENCYRESPONSE MEASUREMENTS• Isolation (Reverse Gain/Loss)

• Large Signal Gain

• Maximum Output Power

• Gain Compression

• Noise Figure

• Harmonic Distortion

• Etc.2626

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CHARACTERIZATION OF NON-LINEAR NETWORKS

Mixers and Frequency Translators

I--+-.... IF

LO

,1_J ...

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2.4 CHARACTERIZATION OFNON-LINEAR NETWORKS

Mixers and frequency translatorsare usually considered non-linearnetworks even though their frequen­cy response is measured as if theywere linear components.

The flatness of the conversion fromRF to IF port (as a function of RFor LO frequency). as well as thefrequency response for various LOdrive levels has to be established.

IF Signal Level

...

IF Signal Level

LO +10 dBm

~, LO +8 dBm \

...

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RF Frequency....

LO Frequency

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OTHER PARAMETERS• Conversion (Loss) Efficiency

• Compression

• Feedthrough, Isolation, Balance

• Third Order Intercept (TOI)

• Etc.

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A scalar network analyzer is theideal measurement tool to charac­terize these components because ofthe inherent broadband characteris­tic of the receiver.

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A different example of a non-linearnetwork is shown in the followingslides. A voltage controlled at­tenuator (or modulator) is charac­terized as a function of the con­trol signal.

CHARACTERIZATION OF

NON-LINEAR NETWORKS

Voltage Controlled Attenuators

ControlSignal

OutputSignal

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The figure shows attenuationcharacteristic for two differentfrequencies as well as a deviationfrom the desired control functionplot.

Additional examples of componentswhich can be characterized in asimilar fashion are listed below.

Attenuation

...\\\

f, \\,'---

Control Signal

AttenuationControl Signal

Deviation fromDesired Control Function

Control Signal

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OTHER EXAMPLES• Modulator/Demodulator

• AGe Amplifier

• Log Amplifier

• Etc.

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FREQUENCY & TIME DOMAINCHARACTERIZATION

r------iREF

I II I

OUT

..A2636

2.5 FREQUENCY AND TIHE DOHAINCHARACTERIZATION

The Scalar Analyzer concept (homo­dyne receiver) lends itself nicelyto do time and distance domaincharacterization via frequency do­main measurements. An inverseFourier transform computation isused to give the time domaindisplay •

Equal Lengths Unequal Lengths

The basic operating principle isexplained below. The diode detectorconvolves the transmi tted (T) and thereference (REF.) signal resulting ina ripple pattern over the frequencyspan of interest due to the phasing ofthe two microwave vectors.

Frequency

.....Frequency

-...

If the reference and transmitted pathlengths are equal, the resultingswept response would be a flat traceas there is no time delay between thetwo signals. When one path length islonger, a ripple pattern will beexhibited.

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Frequency

Sj

Ref.

Trans.

MultipathII

~Time

Delay = l!..t.t

13

The number of envelop periods (N)divided by the frequency change(delta-f) will indicate the delay ofthe device under test with respect toa reference calibration.

Higher order ripples will occur ifthe signal is reflected and travelsthrough the network again or whenmulti path transmission occursthrough or around the device undertest.

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The major applications for thismeasurement principle are listedhere.

MEASUREMENT APPLICATIONS• Time Delay Measurements

• Fault Location

• Multipath Transmission

• Etc.

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3. PRACTICAL MEASUREMENTAPPLICATIONS

PRACTICAL MEASUREMENT

APPLICATIONS

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3.1 INCREASED DYNAMIC RANGEMEASUREMENTS

INCREASED DYNAMIC RANGE

Instead of only utilizing thedynamic range of our receiver chan­nel (T), the incident signal (1) isalso varied as a function of theattenuation of the device undertest by means of the leveling loop.

As previously mentioned, scalaranalyzers have usually less dynamicrange than vector analyzers do.However, there are ways to signifi­cantly extend the measurement rangeby considering the following testset-up. (8)

+10 dBm

">--oW-TOUT

+10 dBm,r -30

:"11~I IL .....J

Leveling (+ 10 - 30 dBm)

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SIGNAL LEVELS AS A FUNCTIONOF OUT ATTENUATION:

For high attenuation, the amplifierin the test path brings the signallevel up by 40 dB at the same timethe source puts out its maximumpower (+10 dBm).

OUT Loss Incident Transmitted

CD o dB -40 dBm + 10 dBm20 -20 +10

® 40 0 +1060 0 -1080 0 -30

@ 100 0 -50

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devicetrans­simul­is re­to ex­output

For low attenuation of theunder test, the (amplified)mit ted signal rises andtaneously the source powerduced via leveling loop notceed the maximum measureablesignal.

The ratio Til therefore varies from+50 to -50 dB thus displaying 100dBof dynamic range.

Frequency

A(w) of OUT

o dB

-100 dB

-50 dB

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3.2 GAIN COMPRESSION MEASUREMENTSON AMPLIFIERS

The next example shows an applica­tion where the network has to becharacterized as a function of sig­nal level to establish the maximumundistorted output power or at whatinput (or output) level the gaindrops by a given amount. For exam­ple. by 1 dB which is called the1dB compression point.

GAIN COMPRESSION MEASUREMENTA. Versus Signal Level (Fixed Frequency)

t----+.--~T ~ P~,

Sweep InputPower Leveland Measure Gain vs. p," or P••,

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Gain Compression (a) vs.Level (b) V5. Frequency

Compression

P~, (Set) t

Frequency

Gain

p... or P~

Signal Level

GAIN!I

The test is done in two steps:a) as a function of signal level

at a constant frequency. andb) as a function of frequency at

a certain output level.

(a) (b)

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l

OUT

t--~...-~ T ~ P~,

~ 11~ALC ------:-I------}) I ~ P~

I IL .J

B. Versus Frequency (Fixed Power)

The set-up for the latter measure­ment is shown here and includes theleveling loop to establish adesired power level at the output.The display indicates gain compres­sion as a function of frequency forthis set output power.

Set Desired Output Powerand Measure Gain vs. Frequency

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REFLECTION MEASUREMENT

3.3 REFLECTION MEASUREMENT WITHTHE LONG LINE OR RIPPLETECHNIQUE

Long line or Ripple Method

Example: Slotted Line

As shown in the first paragraph,scalar reflection measurements areusually taken by inserting a direc­tional bridge or coupler as a sig­nal separation device in front ofthe device under test. Comparingthe incident (I) and reflected (R)signal leads to the measuredreflection coefficient of the net­work, which includes the ambigu­ities due to directivity (D) andtest port match of the set up.

Device Under Test

R

Reflected Ir,le-.' + 0,

IIII

...~.------ .........~ IChange ProbePosition

Slotted Line e-w

Probe

Source

ChangeFrequency

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REFLECTION MEASUREMENTVSWR = Em.. =~ r = ~ ? = Irl

Em'" I-R I

In order to understand some of theimprovements and new developmentsin scalar measurements, it may bebeneficial to digress back to theslotted line reflection measure­ments as shown here.

Em,. = I + R The reflection coefficient in thiscase, is determined by measuringthe standing wave pattern along thetransmission line. Unlike in thecase of the reflection measurementwith a directional bridge (or cou­pler), this method is basicallycapable of measuring the complexreflection coefficient gamma (withthe appropriate calibration andsome computational effort).

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M = V12 + R2 - 2 IR cos 0

o = 2{3f - 0 L

_ 360 0 X Frequency{3 - Propagation Velocity

M [em] = ~ = 15 [em]f M [GHz]

M [GHz] = Y.. = 15 [em]f M [em]

Because of the duality betweenstanding wave patterns versusfrequency and length, this methodcan be readily expanded to measurediscontinuities (reflections) incables when the frequency is var-ied. By scaling the electricallength (1) with the appropriatepropagation velocity, the locationof the discontinuity can be calcu­lated (e.g., open end of cable).

Llt [ns](Round Trip)

2M=v

= M [em] =15 [em]

2M [GHz]

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3.4 MULTIPLE REFLECTIONS ANDFAULT LOCATION

REFLECTION MEASUREMENTThe measurement concept just dis­cussed can be expanded to resolvemultiple reflections. Depending onthe location and size of discon­tinuities, the scalar analyzer willshow a superposition of ripple pat­terns which can be analyzed by ex­tracting the indivivual mismatchripples.

Multiple Reflectionsand Fault Location '1 '2

The inverse Fourier transform (withthe appropropriate windowing) willconvert the ripple pattern in indi­vidual impluse functions spacedaccording to the electrical lengthof the position of the discon­tinuites along the propagationpath.

The resolution in the time or dis­tance domain is obviously inverselyproportional to the higher frequen­cy component of the test signal(@ 20 GHz A 1.5cm or .05ns).

In summary, scalar measurementswere presented as an economicalalternative for many microwave andRF measurements. We coveredseveral general and some specificapplications, and we will demon­strate some examples with the as­sociated hardware and software atthe exhibits. (9)( 10)

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......1------1'3-------1~

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r Ir,l

Separation of Components .... Fourier Transform

-- Time or Distance Domain Display

Ripple

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SUMMARY ANDCONCLUSIONS

• Scalar Measurements Are anEconomical Alternative to MostMicrowave Measurements

• Several Advanced MeasurementApplications Were Discussed

• Hardware and SoftwareDemonstrations Will Be Givenat the Exhibits

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REFERENCES

1. Hewlett-Packard Journal, November 1972

2. Hewlett Packard Journal, July 1976

3. Stephen F. Adam, MICROWAVE THEORY AND APPLICATIONS(Prentice-Hall, Inc., 1969)

4. Ray J. King, MICROWAVE HOMODYNE SYSTEMS (Peter Peregrinus,Ltd., 1978)

5. Kenneth K. Clarke and Donald T. Hess, COMMUNICATION CIRCUITS(Addison-Wesley, 1978)

6. HP MICROWAVE SCALAR NETWORK MEASUREMENT SEMINAR 1985

7. B. Eicher and C. Staeger, A SURVEY OF REFLECTION MEASUREMENTMETHODS (Technische Mitteilungen PTT, 1982)

8. HP Application Note #327-1

9. 8756A Operating and Service Manual (1983)

10. 85015A Systems Software Operating Manual (1983)

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March 1985

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