Keysight Technologies Spectrum Analysis Basics
Keysight TechnologiesSpectrum Analysis BasicsApplication Note 150
2 Keysight Spectrum Analysis Basics – Application Note 150Keysight Technologies. Inc. dedicates this application note to Blake Peterson.Blake’s outstanding service in technical support reached customers in all corners ofthe world during and after his 45-year career with Hewlett-Packard and Keysight. Formany years, Blake trained new marketing and sales engineers in the “ABCs” of spectrumanalyzer technology, which provided the basis for understanding more advancedtechnology. He is warmly regarded as a mentor and technical contributor in spectrumanalysis.Blake’s many accomplishments include:–– Authored the original edition of the Spectrum Analysis Basics application note andcontributed to subsequent editions–– Helped launch the 8566/68 spectrum analyzers, marking the beginning ofmodern spectrum analysis, and the PSA Series spectrum analyzers that set newperformance benchmarks in the industry when they were introduced–– Inspired the creation of Blake Peterson University––required training for allengineering hires at KeysightAs a testament to his accomplishments and contributions, Blake was honored withMicrowaves & RF magazine’s first Living Legend Award in 2013.
3 Keysight Spectrum Analysis Basics – Application Note 150Table of ContentsChapter 1 – Introduction – What Is A Spectrum Analyzer?.5Frequency domain versus time domain .5What is a spectrum? .6Why measure spectra? .6Types of signal analyzers .8Chapter 2 – Spectrum Analyzer Fundamentals .9RF attenuator.10Low-pass filter or preselector.10Tuning the analyzer .11IF gain.12Resolving signals.13Residual FM.15Phase noise.16Sweep time.18Envelope detector .20Displays.21Detector types.22Sample detection.23Peak (positive) detection.24Negative peak detection.24Normal detection.24Average detection.27EMI detectors: average and quasi-peak detection.27Averaging processes.28Time gating.31Chapter 3 – Digital IF Overview .36Digital filters.36All-digital IF.37Custom digital signal processing.38Additional video processing features .38Frequency counting .38More advantages of all-digital IF.39Chapter 4 – Amplitude and Frequency Accuracy.40Relative uncertainty .42Absolute amplitude accuracy.42Improving overall uncertainty.43Specifications, typical performance and nominal values.43Digital IF architecture and uncertainties.43Amplitude uncertainty examples.44Frequency accuracy.44
4 Keysight Spectrum Analysis Basics – Application Note 150Table of ContentscontinuedChapter 5 – Sensitivity and Noise. 46Sensitivity. 46Noise floor extension. 48Noise figure. 49Preamplifiers. 50Noise as a signal. 53Preamplifier for noise measurements. 54Chapter 6 – Dynamic Range. 55Dynamic range versus internal distortion . 55Attenuator test. 57Noise. 57Dynamic range versus measurement uncertainty. 58Gain compression. 60Display range and measurement range. 60Adjacent channel power measurements. 61Chapter 7 – Extending the Frequency Range. 62Internal harmonic mixing. 62Preselection. 66Amplitude calibration. 68Phase noise . 68Improved dynamic range. 69Pluses and minuses of preselection. 70External harmonic mixing. 71Signal identification. 73Chapter 8 – Modern Signal Analyzers. 76Application-specific measurements. 76The need for phase information. 77Digital modulation analysis. 79Real-time spectrum analysis. 80Chapter 9 – Control and Data Transfer. 81Saving and printing data. 81Data transfer and remote instrument control . 81Firmware updates. 82Calibration, troubleshooting, diagnostics and repair. 82Summary. 82Glossary of Terms. 83
5 Keysight Spectrum Analysis Basics – Application Note 150Chapter 1. Introduction - What Is A Spectrum Analyzer?This application note explains thefundamentals of swept-tuned,superheterodyne spectrum analyzers anddiscusses the latest advances in spectrumanalyzer capabilities.At the most basic level, a spectrumanalyzer can be described as a frequencyselective, peak-responding voltmetercalibrated to display the rms value of asine wave. It is important to understandthat the spectrum analyzer is not a powermeter, even though it can be used todisplay power directly. As long as we knowsome value of a sine wave (for example,peak or average) and know the resistanceacross which we measure this value, we cancalibrate our voltmeter to indicate power.With the advent of digital technology,modern spectrum analyzers have beengiven many more capabilities. In this note,we describe the basic spectrum analyzeras well as additional capabilities madepossible using digital technology and digitalsignal processing.Fourier1 theory tells us any time-domainelectrical phenomenon is made up ofone or more sine waves of appropriatefrequency, amplitude, and phase.In other words, we can transform atime-domain signal into its frequencydomain equivalent. Measurements in thefrequency domain tell us how much energyis present at each particular frequency.With proper filtering, a waveform suchas the one shown in Figure 1-1 can bedecomposed into separate sinusoidalwaves, or spectral components, which wecan then evaluate independently. Eachsine wave is characterized by its amplitudeand phase. If the signal we wish to analyzeis periodic, as in our case here, Fouriersays that the constituent sine waves areseparated in the frequency domain by 1/T,where T is the period of the signal 2.Some measurements require that wepreserve complete information aboutthe signal frequency, amplitude andphase. However, another large groupof measurements can be made withoutknowing the phase relationships amongthe sinusoidal components. This type ofsignal analysis is called spectrum analysis.Because spectrum analysis is simplerto understand, yet extremely useful, webegin by looking first at how spectrumanalyzers perform spectrum analysismeasurements, starting in Chapter 2.Theoretically, to make the transformationfrom the time domain to the frequencydomain, the signal must be evaluated overall time, that is, over infinity. However, inpractice, we always use a finite time periodwhen making a measurement.Frequency domain versustime domainBefore we get into the details ofdescribing a spectrum analyzer, wemight first ask ourselves: “Just whatis a spectrum and why would we wantto analyze it?” Our normal frame ofreference is time. We note when certainevents occur. This includes electricalevents. We can use an oscilloscopeto view the instantaneous value of aparticular electrical event (or someother event converted to volts throughan appropriate transducer) as a functionof time. In other words, we use theoscilloscope to view the waveform of asignal in the time domain.Figure 1-1. Complex time-domain signal1.2.Jean Baptiste Joseph Fourier, 1768-1830. A French mathematician and physicist who discovered that periodic functions can be expanded into a series ofsines and cosines.If the time signal occurs only once, then T is infinite, and the frequency representation is a continuum of sine waves.
6 Keysight Spectrum Analysis Basics – Application Note 150You also can make Fourier transformationsfrom the frequency to the time domain.This case also theoretically requires theevaluation of all spectral components overfrequencies to infinity. In reality, makingmeasurements in a finite bandwidththat captures most of the signal energyproduces acceptable results. When youperform a Fourier transformation onfrequency domain data, the phase of theindividual components is indeed critical.For example, a square wave transformedto the frequency domain and back againcould turn into a sawtooth wave if you donot preserve phase.What is a spectrum?So what is a spectrum in the context ofthis discussion? A spectrum is a collectionof sine waves that, when combinedproperly, produce the time-domain signalunder examination. Figure 1-1 shows thewaveform of a complex signal. Supposethat we were hoping to see a sine wave.Although the waveform certainly showsus that the signal is not a pure sinusoid, itdoes not give us a definitive indication ofthe reason why.Figure 1-2 shows our complex signal inboth the time and frequency domains.The frequency-domain display plots theamplitude versus the frequency of eachsine wave in the spectrum. As shown, thespectrum in this case comprises just twosine waves. We now know why our originalwaveform was not a pure sine wave. Itcontained a second sine wave, the secondharmonic in this case. Does this mean wehave no need to perform time-domainmeasurements? Not at all. The timedomain is better for many measurements,and some can be made only in the timedomain. For example, pure time-domainmeasurements include pulse rise and falltimes, overshoot and ringing.People involved in wireless communicationsare extremely interested in out-of-bandand spurious emissions. For example,cellular radio systems must be checked forharmonics of the carrier signal that mightinterfere with other systems operating atthe same frequencies as the harmonics.Engineers and technicians are also veryconcerned about distortion of the messagemodulated onto a carrier.Why measure spectra?Spectrum monitoring is another importantfrequency-domain measurement activity.Government regulatory agencies allocatedifferent frequencies for various radioservices, such as broadcast television andradio, mobile phone systems, police andemergency communications, and a host ofother applications. It is critical that eachof these services operates at the assignedfrequency and stays within the allocatedchannel bandwidth. Transmitters andother intentional radiators often mustoperate at closely spaced adjacentfrequencies. A key performance measurefor the power amplifiers and othercomponents used in these systems isthe amount of signal energy that spillsover into adjacent channels and causesinterference.The frequency domain also has itsmeasurement strengths. We have alreadyseen in Figures 1-1 and 1-2 that thefrequency domain is better for determiningthe harmonic content of a signal.Frequency domainmeasurementsTime domainmeasurementsFigure 1-2. Relationship between time and frequency domainFigure 1-2.Third-order intermodulation (two tones ofa complex signal modulating each other)can be particularly troublesome becausethe distortion components can fall withinthe band of interest, which means theycannot be filtered away.Electromagnetic interference (EMI) isa term applied to unwanted emissionsfrom both intentional and unintentionalradiators. These unwanted emissions,either radiated or conducted (throughthe power lines or other interconnectingwires), might impair the operation ofother systems. Almost anyone designingor manufacturing electrical or electronicproducts must test for emission levelsversus frequency according to regulationsset by various government agencies orindustry-standard bodies.
7 Keysight Spectrum Analysis Basics – Application Note 150Figure 1-3. Harmonic distortion test of a transmitterFigure 1-4. GSM radio signal and spectral mask showing limits ofunwanted emissionsFigure 1- 5. Two-tone test on an RF power amplifierFigure 1-6. Radiated emissions plotted against CISPR11 limits as part of anEMI test
8 Keysight Spectrum Analysis Basics – Application Note 150Noise is often the signal you want tomeasure. Any active circuit or devicewill generate excess noise. Tests suchas noise figure and signal-to-noise ratio(SNR) are important for characterizingthe performance of a device andits contribution to overall systemperformance.Figures 1-3 through 1-6 show some ofthese measurements on an X-Seriessignal analyzer.Types of signal analyzersThe first swept-tuned superheterodyneanalyzers measured only amplitude.However, as technology advancedand communication systems grewmore complex, phase became a moreimportant part of the measurement.Spectrum analyzers, now often labeledsignal analyzers, have kept pace. Bydigitizing the signal, after one or morestages of frequency conversion, phase aswell as amplitude is preserved and canbe included as part of the informationdisplayed. So today’s signal analyzerssuch as the Keysight X-Series combine theattributes of analog, vector and FFT (fastFourier transform) analyzers. To furtherimprove capabilities, Keysight’s X-Seriessignal analyzers incorporate a computer,complete with a removable disk drivethat allows sensitive data to remain in acontrolled area should the analyzer beremoved.Advanced technology also has allowedcircuits to be miniaturized. As a result,rugged portable spectrum analyzers suchas the Keysight FieldFox simplify tasks suchas characterizing sites for transmittersor antenna farms. Zero warm-up timeeliminates delays in situations involvingbrief stops for quick measurements. Dueto advanced calibration techniques, fieldmeasurements made with these handheldanalyzers correlate with lab-grade benchtop spectrum analyzers within 10ths of a dB.In this application note, we concentrateon swept amplitude measurements,only briefly touching on measurementsinvolving phase–see Chapter 8.Note: When computers became HewlettPackard’s dominant business, it createdand spun off Keysight Technologies inthe late 1990’s to continue the test andmeasurement business. Many olderspectrum analyzers carry the HewlettPackard name but are supported byKeysight.This application note will give you insightinto your particular spectrum or signalanalyzer and help you use this versatileinstrument to its maximum potential.More informationFor additional information on vectormeasurements, see Vector SignalAnalysis Basics–Application Note, literaturenumber 5989-1121EN. For informationon FFT analyzers that tune to 0 Hz,see the Web page for the Keysight35670A atwww.keysight.com/find/35670A.
9 Keysight Spectrum Analysis Basics – Application Note 150Chapter 2. Spectrum Analyzer FundamentalsThis chapter focuses on the fundamentaltheory of how a spectrum analyzerworks. While today’s technology makes itpossible to replace many analog circuitswith modern digital implementations, itis useful to understand classic spectrumanalyzer architecture as a starting point inour discussion.In later chapters, we will look at thecapabilities and advantages that digitalcircuitry brings to spectrum analysis.Chapter 3 discusses digital architecturesused in spectrum analyzers availabletoday.Figure 2-1 is a simplified block diagramof a superheterodyne spectrum analyzer.Heterodyne means to mix; that is, totranslate frequency. And super refers tosuperaudio frequencies, or frequenciesabove the audio range. In the Figure2-1 block diagram, we see that an inputsignal passes through an attenuator,then through a low-pass filter (later wewill see why the filter is here) to a mixer,where it mixes with a signal from the localoscillator (LO).RF inputattenuatorBecause the mixer is a non-linear device,its output includes not only the twooriginal signals, but also their harmonicsand the sums and differences of theoriginal frequencies and their harmonics.If any of the mixed signals falls within thepass band of the intermediate-frequency(IF) filter, it is further processed (amplifiedand perhaps compressed on a logarithmicscale). It is essentially rectified by theenvelope detector, filtered throughthe low-pass filter and displayed. Aramp generator creates the horizontalmovement across the display from left toright. The ramp also tunes the LO so itsfrequency change is in proportion to theramp voltage.If you are familiar with superheterodyneAM radios, the type that receive ordinaryAM broadcast signals, you will note astrong similarity between them andthe block diagram shown in Figure 2-1.The differences are that the output of aspectrum analyzer is a display instead ofa speaker, and the local oscillator is tunedelectronically rather than by a front-panelknob.MixerIF gainIF filterThe output of a spectrum analyzer is anX-Y trace on a display, so let’s see whatinformation we get from it. The displayis mapped on a grid (graticule) with 10major horizontal divisions and generally10 major vertical divisions. The horizontalaxis is linearly calibrated in frequency thatincreases from left to right. Setting thefrequency is a two-step process. First weadjust the frequency at the centerline ofthe graticule with the center frequencycontrol. Then we adjust the frequencyrange (span) across the full 10 divisionswith the frequency span control. Thesecontrols are independent, so if we changethe center frequency, we do not alter thefrequency span. Alternatively, we can setthe start and stop frequencies insteadof setting center frequency and span.In either case, we can determine theabsolute frequency of any signal displayedand the relative frequency differencebetween any two tor, orlow-pass rSweepgeneratorFigure 2-1. Block diagram of a classic superheterodyne spectrum analyzerDisplay
10 Keysight Spectrum Analysis Basics – Application Note 150The vertical axis is calibrated in amplitude.You can choose a linear scale calibratedin volts or a logarithmic scale calibratedin dB. The log scale is used far moreoften than the linear scale because ithas a much wider usable range. Thelog scale allows signals as far apart inamplitude as 70 to 100 dB (voltage ratiosof 3200 to 100,000 and power ratios of10,000,000 to 10,000,000,000) to bedisplayed simultaneously. On the otherhand, the linear scale is usable for signalsdiffering by no more than 20 to 30 dB(voltage ratios of 10 to 32). In either case,we give the top line of the graticule, thereference level, an absolute value throughcalibration techniques1 and use thescaling per division to assign values toother locations on the graticule. Therefore,we can measure either the absolutevalue of a signal or the relative amplitudedifference between any two signals.The blocking capacitor is used to preventthe analyzer from being damaged by a DCsignal or a DC offset of the signal beingviewed. Unfortunately, it also attenuateslow-frequency signals and increases theminimum useable start frequency of theanalyzer to 9 kHz, 100 kHz or 10 MHz,depending on the analyzer.In some analyzers, an amplitude referencesignal can be connected as shown inFigure 2-3. It provides a precise frequencyand amplitude signal, used by the analyzerto periodically self-calibrate.Low-pass filter or preselectorThe low-pass filter blocks high-frequencysignals from reaching the mixer. Thisfiltering prevents out-of-band signalsfrom mixing with the local oscillator andcreating unwanted responses on thedisplay. Microwave spectrum analyzersreplace the low-pass filter with apreselector, which is a tunable filter thatrejects all frequencies except those wecurrently wish to view. In Chapter 7, we gointo more detail about the operation andpurpose of the preselector.Scale calibration, both frequency andamplitude, is shown by annotationswritten onto the display. Figure 2-2 showsthe display of a typical analyzer.Now, let’s turn our attention back to thespectrum analyzer components diagramedin Figure 2-1.RF attenuatorThe first part of our analyzer is theRF input attenuator. Its purpose is toensure the signal enters the mixer at theoptimum level to prevent overload, gaincompression and distortion. Becauseattenuation is a protective circuit for theanalyzer, it is usually set automatically,based on the reference level. However,manual selection of attenuation is alsoavailable in steps of 10, 5, 2, or even 1 dB.The diagram in Figure 2-3 is an exampleof an attenuator circuit with a maximumattenuation of 70 dB in increments of 2 dB.Figure 2-2. Typical spectrum analyzer display with control settings0 to 70 dB, 2 dB stepsRF inputAmplitudereferencesignalFigure 2-3. RF input attenuator circuitryfigure 2-31.See Chapter 4, “Amplitude and Frequency Accuracy.”
11 Keysight Spectrum Analysis Basics – Application Note 150Tuning the analyzerWe need to know how to tune ourspectrum analyzer to the desiredfrequency range. Tuning is a function ofthe center frequency of the IF filter, thefrequency range of the LO and the rangeof frequencies allowed to reach the mixerfrom the outside world (allowed to passthrough the low-pass filter). Of all themixing products emerging from the mixer,the two with the greatest amplitudes,and therefore the most desirable, arethose created from the sum of the LOand input signal and from the differencebetween the LO and input signal. If we canarrange things so that the signal we wishto examine is either above or below the LOfrequency by the IF, then only one of thedesired mixing products will fall within thepass-band of the IF filter and be detectedto create an amplitude response on thedisplay.We need to pick an LO frequency and anIF that will create an analyzer with thedesired tuning range. Let’s assume thatwe want a tuning range from 0 to 3.6GHz. We then need to choose the IF. Let’stry a 1-GHz IF. Because this frequencyis within our desired tuning range, wecould have an input signal at 1 GHz.The output of a mixer also includes theoriginal input signals, so an input signalat 1 GHz would give us a constant outputfrom the mixer at the IF. The 1-GHz signalwould thus pass through the system andgive us a constant amplitude responseon the display regardless of the tuningof the LO. The result would be a hole inthe frequency range at which we couldnot properly examine signals because theamplitude response would be independentof the LO frequency. Therefore, a 1-GHz IFwill not work.Instead, we choose an IF that is abovethe highest frequency to which we wishto tune. In the Keysight X-Series signalanalyzers that can tune to 3.6 GHz, thefirst LO frequency range is 3.8 to 8.7 GHz,and the I
– Authored the original edition of the Spectrum Analysis Basics application note and contributed to subsequent editions – Helped launch the 8566/68 spectrum analyzers, marking the beginning of modern spectrum analysis, and the PSA Series spectrum analyzers that set new performance benchmarks in the industry when they were introduced
We will begin with an overview of spectrum analysis. In this section, we will define spectrum analysis as well as present a brief introduction to the types of tests that are made with a spectrum analyzer. From there, we will learn about spectrum analyzers in term s of File Size: 1MBPage Count: 86Explore furtherSpectrum Analysis Basics, Part 1 - What is a Spectrum .blogs.keysight.comSpectrum Analysis Basics (AN150) Keysightwww.keysight.comSpectrum Analyzer : Working Principle, Classfication & Its .www.elprocus.comFundamentals of Spectrum Analysis - TU Delftqtwork.tudelft.nlRecommended to you b
Specifications Specifications¹ Keysight 423B Keysight 8473B Keysight 8473C Keysight 8470B Keysight 8472B Frequency range 2 0.01 to 12.4 GHz 0.01 to 18 GHz 0.01 to 26.5 GHz 0.01 to 18 GHz 0.00 to 18 GHz Frequency response Octave band flatness (over any octave 0 01 to 8 GHz) 0.2 dB 0.2 dB 0.2 dB 0.2 dB 0.2 dB
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