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Spectrum Analyzer Basics
Spectrum Analyzer Basics www. agilent.com/find/backtobasics
Abstract
Learn why spectrum analysis is important for a variety of applications and how to measure system
and device performance using a spectrum analyzer. To introduce you to spectrum analyzers, the
theory of operation will be discussed. In addition, the major components inside the analyzer and
why they are important will be examined. Next, you will learn the spectrum analyzer specifications
that are important for your application. Finally, features of a spectrum analyzer that make it more
effective in making measurements will be introduced.
Agenda
Overview:
What is spectrum analysis?
What measurements do we make?
Theory of Operation:
Spectrum analyzer hardware
Specifications:
Which are important and why?
Features
Making the analyzer more effective
Summary
Appendix
Spectrum Analyzer Basics www.agilent.com/find/backtobasics
Slide 1
This paper is intended to be a beginning tutorial on spectrum analysis. It is written for those who are unfamiliar with
spectrum analyzers, and would like a basic understanding of how they work, what you need to know to use them to
their fullest potential, and how to make them more effective for particular applications.
It is written for new engineers and technicians, therefore a basic understanding of electrical concepts is recommended.
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 terms of the hardware inside, what the importance of each
component is, and how it all works together.
In order to make measurements on a spectrum analyzer and to interpret the results correctly, it is important to
understand the characteristics of the analyzer. Spectrum analyzer specifications will help you determine if a particular
instrument will make the measurements you need to make, and how accurate the results will be.
Spectrum analyzers also have many additional features that help make them more effective for particular applications.
We will discuss briefly, some of the more important and widely used features in this section.
And finally, we will wrap up with a summary.
3-1
Agenda
Overview
Theory of Operation
Specifications
Features
Summary
Appendix
Spectrum Analyzer Basics www.agilent.com/find/backtobasics
Slide 2
Let's begin with an overview of spectrum analysis.
3-2
Overview
What is Spectrum Analysis?
8563A SPECTRU M A NALYZER 9 kH z - 2 6.5 GH z
Spectrum Analyzer Basics www.agilent.com/find/backtobasics
Slide 3
If you are designing, manufacturing, or doing field service/repair of electrical devices or systems, you need a tool that
will help you analyze the electrical signals that are passing through or being transmitted by your system or device. By
analyzing the characteristics of the signal once its gone through the device/system, you can determine the performance,
find problems, troubleshoot, etc.
How do we measure these electrical signals in order to see what happens to them as they pass through our
device/system and therefore verify the performance? We need a passive receiver, meaning it doesn't do anything to the
signal - it just displays it in a way that makes it easy to analyze the signal. This is called a spectrum analyzer.
Spectrum analyzers usually display raw, unprocessed signal information such as voltage, power, period, waveshape,
sidebands, and frequency. They can provide you with a clear and precise window into the frequency spectrum.
Depending upon the application, a signal could have several different characteristics. For example, in communications, in
order to send information such as your voice or data, it must be modulated onto a higher frequency carrier. A
modulated signal will have specific characteristics depending on the type of modulation used. When testing non-linear
devices such as amplifiers or mixers, it is important to understand how these create distortion products and what these
distortion products look like. Understanding the characteristics of noise and how a noise signal looks compared to other
types of signals can also help you in analyzing your device/system.
Understanding the important aspects of a spectrum analyzer for measuring all of these types of signals will help you
make more accurate measurements and give you confidence that you are interpreting the results correctly.
3-3
Overview
Types of Tests Made .
Modulation
Noise
Distortion
Spectrum Analyzer Basics www.agilent.com/find/backtobasics
Slide 4
The most common spectrum analyzer measurements are: modulation, distortion, and noise.
Measuring the quality of the modulation is important for making sure your system is working properly and that the
information is being transmitted correctly. Understanding the spectral content is important, especially in
communications where there is very limited bandwidth. The amount of power being transmitted (for example, to
overcome the channel impairments in wireless systems) is another key measurement in communications. Tests such as
modulation degree, sideband amplitude, modulation quality, occupied bandwidth are examples of common modulation
measurements.
In communications, measuring distortion is critical for both the receiver and transmitter. Excessive harmonic distortion
at the output of a transmitter can interfere with other communication bands. The pre-amplification stages in a receiver
must be free of intermodulation distortion to prevent signal crosstalk. An example is the intermodulation of cable TV
carriers that moves down the trunk of the distribution system and distorts other channels on the same cable. Common
distortion measurements include intermodulation, harmonics, and spurious emissions.
Noise is often the signal you want to measure. Any active circuit or device will generate noise. Tests such as noise
figure and signal-to-noise ratio (SNR) are important for characterizing the performance of a device and/or its
contribution to overall system noise.
For all of these spectrum analyzer measurements, it is important to understand the operation of the spectrum analyzer
and the spectrum analyzer performance required for your specific measurement and test specifications. This will help
you choose the right analyzer for your application as well as get the most out of it.
3-4
Overview
Frequency versus Time Domain
Amplitude
ency
(power) frequ
tim
e
Time domain
Frequency Domain
Measurements
Measurements
Spectrum Analyzer Basics www.agilent.com/find/backtobasics
Slide 5
Traditionally, when you want to look at an electrical signal, you use an oscilloscope to see how the signal varies with time. This is very
important information; however, it doesn't give you the full picture. To fully understand the performance of your device/system, you will also
want to analyze the signal(s) in the frequency-domain. This is a graphical representation of the signal's amplitude as a function of frequency
The spectrum analyzer is to the frequency domain as the oscilloscope is to the time domain. (It is important to note that spectrum analyzers
can also be used in the fixed-tune mode (zero span) to provide time-domain measurement capability much like that of an oscilloscope.)
The figure shows a signal in both the time and the frequency domains. In the time domain, all frequency components of the signal are summed
together and displayed. In the frequency domain, complex signals (that is, signals composed of more than one frequency) are separated into
their frequency components, and the level at each frequency is displayed.
Frequency domain measurements have several distinct advantages. For example, let's say you're looking at a signal on an oscilloscope that
appears to be a pure sine wave. A pure sine wave has no harmonic distortion. If you look at the signal on a spectrum analyzer, you may find
that your signal is actually made up of several frequencies. What was not discernible on the oscilloscope becomes very apparent on the
spectrum analyzer.
Some systems are inherently frequency domain oriented. For example, many telecommunications systems use what is called Frequency
Division Multiple Access (FDMA) or Frequency Division Multiplexing (FDM). In these systems, different users are assigned different
frequencies for transmitting and receiving, such as with a cellular phone. Radio stations also use FDM, with each station in a given
geographical area occupying a particular frequency band. These types of systems must be analyzed in the frequency domain in order to make
sure that no one is interfering with users/radio stations on neighboring frequencies. We shall also see later
how measuring with a frequency domain analyzer can greatly reduce the amount of noise present in the measurement because of its ability to
narrow the measurement bandwidth.
From this view of the spectrum, measurements of frequency, power, harmonic content, modulation, spurs, and noise can easily be made.
Given the capability to measure these quantities, we can determine total harmonic distortion, occupied bandwidth, signal stability, output
power, intermodulation distortion, power bandwidth, carrier-to-noise ratio, and a host of other measurements, using just a spectrum analyzer.
3-5
Overview
Different Types of Analyzers
Fourier Analyzer
Parallel filters measured simultaneously
A
LCD shows full spectral
display
f1 f2 f
Spectrum Analyzer Basics www.agilent.com/find/backtobasics
Slide 6
Now that we understand why spectrum analyzers are important, let's take a look at the different types of analyzers
available for measuring RF.
There are basically two ways to make frequency domain measurements (what we call spectrum analysis): Fourier
transform and swept-tuned.
The Fourier analyzer basically takes a time-domain signal, digitizes it using digital sampling, and then performs the
mathematics required to convert it to the frequency domain*, and display the resulting spectrum. It is as if the analyzer
is looking at the entire frequency range at the same time using parallel filters measuring simultaneously. It is actually
capturing the time domain information which contains all the frequency information in it. With its real-time signal
analysis capability, the Fourier analyzer is able to capture periodic as well as random and transient events. It also can
provide significant speed improvement over the more traditional swept analyzer and can measure phase as well as
magnitude. However it does have its limitations, particularly in the areas of frequency range, sensitivity, and dynamic
range. We shall discuss what these terms are and why they are important in a later section.
Fourier analyzers are becoming more prevalent, as analog-to-digital converters (ADC) and digital signal processing (DSP)
technologies advance. Operations that once required a lot of custom, power-hungry discrete hardware can now be
performed with commercial off-the-shelf DSP chips, which get smaller and faster every year. These analyzers can offer
significant performance improvements over conventional spectrum analyzers, but often with a price premium.
* The frequency domain is related to the time domain by a body of knowledge generally known as Fourier theory (named
for Jean Baptiste Joseph Fourier, 1768-1830). Discrete, or digitized signals can be transformed into the frequency
domain using the discrete Fourier transform.
3-6
Overview
Different Types of Analyzers
Swept Analyzer
Filter 'sweeps' over range of
interest
A
LCD shows full
spectral display
f1 f2 f
Spectrum Analyzer Basics www.agilent.com/find/backtobasics
Slide 7
The most common type of spectrum analyzer is the swept-tuned receiver. It is the most widely accepted, general-
purpose tool for frequency-domain measurements. The technique most widely used is superheterodyne. Heterodyne
means to mix - that is, to translate frequency - and super refers to super-audio frequencies, or frequencies above the
audio range. Very basically, these analyzers "sweep" across the frequency range of interest, displaying all the
frequency components present. We shall see how this is actually accomplished in the next section. The swept-tuned
analyzer works just like the AM radio in your home except that on your radio, the dial controls the tuning and instead of
a display, your radio has a speaker.
The swept receiver technique enables frequency domain measurements to be made over a large dynamic range and a
wide frequency range, thereby making significant contributions to frequency-domain signal analysis for numerous
applications, including the manufacture and maintenance of microwave communications links, radar,
telecommunications equipment, cable TV systems, and broadcast equipment; mobile communication systems; EMI
diagnostic testing; component testing; and signal surveillance.
For the remainder of this paper, the term spectrum analyzer will refer only to the swept tuned analyzer. This is the type
of analyzer that we will learn about in detail.
3-7
Agenda
Overview
Theory of Operation
Specifications
Features
Summary
Appendix
Spectrum Analyzer Basics www.agilent.com/find/backtobasics
Slide 8
Based on the previous slide, you might be picturing the inside of the analyzer consisting of a bandpass filter that sweeps
across the frequency range of interest. If the input signal is say, 1 MHz, then when the bandpass filter passes over 1
MHz, it will "see" the input signal and display it on the screen.
Although this concept would work, it is very difficult and therefore expensive to build a filter which tunes over a wide
range. An easier, and therefore less expensive, implementation is to use a tunable local oscillator (LO), and keep the
bandpass filter fixed. We will see when we go into more detail, that in this concept, we are sweeping the input signal
past the fixed filter, and as it passes through the fixed bandpass filter, it is displayed on the screen. Don't worry if it
seems confusing now - as we discuss the block diagram, the concept will become clearer.
Let's now go into more detail as to how the swept spectrum analyzer works.
3-8
Theory of Operation
Spectrum Analyzer Block Diagram
RF input
attenuator IF gain IF filter
mixer detector
Input
signal
Pre-Selector
Log
Or Low Pass Amp
Filter video
filter
local
oscillator
sweep
generator
Crystal
Reference CRT display
Spectrum Analyzer Basics www.agilent.com/find/backtobasics
Slide 9
The major components in a spectrum analyzer are the RF input attenuator, mixer, IF (Intermediate Frequency) gain, IF
filter, detector, video filter, local oscillator, sweep generator, and LCD display. Before we talk about how these pieces
work together, let's get a fundamental understanding of each component individually.
3-9
Theory of Operation MIXER
Mixer
input
f LO - f sig f LO + f sig
RF IF
f sig
LO f sig f LO
f LO
Spectrum Analyzer Basics www.agilent.com/find/backtobasics
Slide 10
We'll start with the mixer
A mixer is a three-port device that converts a signal from one frequency to another (sometimes called a frequency
translation device).
We apply the input signal to one input port, and the Local Oscillator signal to the other.
By definition, a mixer is a non-linear device, meaning that there will be frequencies at the output that were not present
at the input.
The output frequencies that will be produced by the mixer are the original input signals, plus the sum and difference
frequencies of these two signals.
It is the difference frequency that is of interest in the spectrum analyzer, which we will see shortly. We call this signal
the IF signal, or Intermediate Frequency signal.
3-10
Theory of Operation IF FILTER
IF Filter
Input
Spectrum
IF Bandwidth
(RBW)
Display
Spectrum Analyzer Basics www.agilent.com/find/backtobasics
Slide 11
The IF filter is a bandpass filter which is used as the "window" for detecting signals. It's bandwidth is also called the
resolution bandwidth (RBW) of the analyzer and can be changed via the front panel of the analyzer.
By giving you a broad range of variable resolution bandwidth settings , the instrument can be optimized for the sweep
and signal conditions, letting you trade-off frequency selectivity (the ability to resolve signals), signal-to-noise ratio
(SNR), and measurement speed.
We can see from the slide that as RBW is narrowed, selectivity is improved (we are able to resolve the two input
signals). This will also often improve SNR. The sweep speed and trace update rate, however, will degrade with
narrower RBWs. The optimum RBW setting depends heavily on the characteristics of the signals of interest.
3-11
Theory of Operation
Detector DETECTOR
amplitude
"bins" Positive detection: largest value
in bin displayed
Negative detection: smallest value
in bin displayed
Sample detection: last value in bin displayed
Spectrum Analyzer Basics www.agilent.com/find/backtobasics
Slide 12
The analyzer must covert the IF signal to a baseband or video signal so it can be digitized and then viewed on the
analyzer display. This is accomplished with an envelope detector whose video output is then digitized with an analog-to-
digital converter (ADC). The digitized output of the ADC is then represented as the signal's amplitude on the Y-axis of
the display. This allows for several different detector modes that dramatically affect how the signal is displayed.
In positive detection mode, we take the peak value of the signal over the duration of one trace element, whereas in
negative detection mode, its the minimum value. Positive detection mode is typically used when analyzing sinusoids,
but is not good for displaying noise, since it will not show the true randomness of the noise.
In sample detection, a random value for each bin is produced. This is best for looking at noise or noise-like signals. For
burst or narrowband signals, it is not a good mode to use, as the analyzer might miss the signals of interest.
When displaying both signals and noise, the best mode is the normal mode, or the rosenfell mode. This is a "smart"
mode, which will dynamically change depending upon the input signal. For example, If the signal both rose and fell
within a sampling bin, it assumes it is noise and will use pos & neg det alternately. If it continues to rise, it assumes a
signal and uses pos peak det.
3-12
Theory of Operation
Video Filter
VIDEO
FILTER
Spectrum Analyzer Basics www.agilent.com/find/backtobasics
Slide 13
The video filter is a low-pass filter that is located after the envelope detector and before the ADC. This filter
determines the bandwidth of the video amplifier, and is used to average or smooth the trace seen on the screen.
The spectrum analyzer displays signal-plus-noise so that the closer a signal is to the noise level, the more the noise
makes the signal more difficult to read. By changing the video bandwidth (VBW) setting, we can decrease the peak-to-
peak variations of noise. This type of display smoothing can be used to help find signals that otherwise might be
obscured in the noise.
3-13
Theory of Operation
Other Components
LO
SWEEP
GEN
frequency
LCD DISPLAY
RF INPUT
ATTENUATOR IF GAIN
Spectrum Analyzer Basics www.agilent.com/find/backtobasics
Slide 14
And finally, a brief description of the last few components.
The local oscillator (LO) s a Voltage Controlled Oscillator (VCO) which in effect tunes the analyzer. The sweep
generator actually tunes the LO so that its frequency changes in proportion to the ramp voltage.
The sampling of the video signal by the ADC is also synchronized with the sweep generator to create the frequency
domain on the x-axis. Because the relationship between the local oscillator and the input signal is known, the horizontal
axis of the display can be calibrated in terms of the input signal's frequency.
The RF input attenuator is a step attenuator located between the input connector and the first mixer. It is also called
the RF attenuator. This is used to adjust the level of the signal incident upon the first mixer. This is important in order
to prevent mixer gain compression and distortion due to high-level and/or broadband signals.
The IF gain is located after the mixer but before the IF, or RBW, filter. This is used to adjust the vertical position of
signals on the display without affecting the signal level at the input mixer. When changed, the value of the reference
level is changed accordingly. Since we do not want the reference level to change (i.e. the vertical position of displayed
signals) when we change the input attenuator, these two components are tied together. The IF gain will automatically
be changed to compensate for input attenuator changes, so signals remain stationary on the LCD display, and the
reference level is not changed.
3-14
Theory of Operation
How it all works together
fs Signal Range LO Range
f LO - f s f LO
0 1 2 3 (GHz) f LO + f s
fs
IF filter
mixer 0 1 fs 2 3 4 5 6 detector
3.6 6.5
input
3.6
f IF
sweep generator A
LO
f LO
0 1 2 3 (GHz) f
3 4 5 6 (GHz) LCD display
3.6 6.5
Spectrum Analyzer Basics www.agilent.com/find/backtobasics
Slide 15
Let's put it all together now. Note that while the RF input attenuator, IF gain, and video filter are important, they are
not critical when describing how the analyzer works.
The signal to be analyzed is connected to the input of the analyzer. This signal is then combined with the LO through the
mixer to convert it to an IF.
These signals are then sent to the IF filter, whose output is detected, indicating the presence of a signal at the
analyzer's tuned frequency.
The output voltage of the detector drives the vertical axis (amplitude) of the LCD display.
The sweep generator provides synchronization between the horizontal axis (frequency) and tuning of the LO.
The resulting display shows amplitude versus frequency of the spectral components of each incoming signal.
Let's see how this works visually.
(Place blocked slide over this one. Show how as the signals pass through the IF filter, they are traced out on the
display.)
3-15
Theory of Operation
Front Panel Operation
Primary functions
(Frequency, Amplitude, Span)
Softkeys
SPECTRU M A NALYZER 9 kH z - 2 6.5 GH z
8563A
Control functions
(RBW, sweep time,
VBW)
RF Input Numeric
keypad
Spectrum Analyzer Basics www.agilent.com/find/backtobasics
Slide 16
Before we move on, its important to know what we can control on the analyzer via the front panel keys.
The three primary hardkeys on any spectrum analyzer are: frequency, amplitude, and span. Obviously, we need to be
able to set up the analyzer for our particular measurement conditions. Frequency and amplitude are straightforward.
Span is simply a way to tell the analyzer how big of a "window" in frequency we want to view.
Other important control functions include setting the resolution bandwidth, sweeptime, input attenuator and video
bandwidth. Modern analyzers have both hardkeys and softkeys (next to the LCD display). The softkeys allow you to
access several different functions/features under one hardkey. For example, there will typically be a hardkey labeled
"BW", which when pressed gives you the choice of changing either the RBW or the VBW depending upon which softkey
you press.
Most analyzers allow you to enter values by either punching in the value on the number pad, or by "dialing" up or down
to the desired value using the front panel knob.
3-16
Agenda
Overview
Theory of Operation
Specifications
Features
Summary
Appendix
Spectrum Analyzer Basics www.agilent.com/find/backtobasics
Slide 17
Understanding the capabilities and limitations of a spectrum analyzer is a very important part of understanding spectrum
analysis. Today's spectrum analyzers offer a great variety of features and levels of performance. Reading a datasheet
can be very confusing. How do you know which specifications are important for your application and why?
Spectrum analyzer specifications are the instruments manufacturer's way of communicating the level of performance
you can expect from a particular instrument. Understanding and interpreting these specifications enables you to predict
how the analyzer will perform in a specific measurement situation.
We will now describe a variety of specifications that are important to understand.
3-17
Specifications
8563A SPECTRU M A NALYZER 9 kH z - 2 6.5 GH z
Frequency Range
Accuracy: Frequency & Amplitude
Resolution
Sensitivity
Distortion
Dynamic Range
Spectrum Analyzer Basics www.agilent.com/find/backtobasics
Slide 18
What do you need to know about a spectrum analyzer in order to make sure you choose one that will make your
particular measurements, and make them adequately? Very basically, you need to know 1) what's the frequency
range? 2) what's the amplitude range (maximum input and sensitivity)? 3) to what level can I measure the difference
between two signals, both in amplitude (dynamic range) and frequency (resolution)? and 4) how accurate are my
measurements once I've made them?
Although not in the same order, we will describe each of these areas in detail in terms of what they mean and why they
are important.
3-18
Specifications
Frequency Range
Low frequencies
for baseband and IF
Measuring harmonics
50 GHz and beyond!
Spectrum Analyzer Basics www.agilent.com/find/backtobasics
Slide 19
Of course, the first and foremost specification you want to know is the frequency range of the analyzer. Not only do
you want a spectrum analyzer that will cover the fundamental frequencies of your application, but don't forget
harmonics or spurious signals on the high end, or baseband and IF on the low end.
An example of needing higher frequency capability is in wireless communications. Some of the cellular standards
require that you measure out to the tenth harmonic of your system. If you're working at 900 MHz, that means you
need an analyzer that has a high frequency of 10 * 900 MHz = 9 GHz. Also, although we are talking about RF
analyzers, you want it to be able to measure your lower frequency baseband and IF signals as well.
3-19
Specifications
Accuracy
Absolute Relative
Amplitude Amplitude
in dBm in dB
Frequency
Relative
Frequency
Spectrum Analyzer Basics www.agilent.com/find/backtobasics
Slide 20
The second area to understand is accuracy; how accurate will my results be in both frequency and amplitude? When
talking about accuracy specifications, it is important to understand that there is both an absolute accuracy
specification, and a relative accuracy specification.
The absolute measurement is made with a single marker. For example, the frequency and power level of a carrier for
distortion measurements is an absolute measurement.
The relative measurement is made with the relative, or delta, marker. Examples include modulation frequencies, channel
spacing, pulse repetition frequencies, and offset frequencies relative to the carrier. Relative measurements are more
accurate than absolute measurements.
Let's begin by discussing frequency accuracy.
3-20
Specifications
Accuracy: Frequency Readout Accuracy
Typical datasheet specification:
Spans < 2 MHz: +
_ (freq. readout x freq. ref. accuracy
+ 1% of frequency span
+ 15% of resolution bandwidth
+ 10 Hz "residual error")
Frequency
Spectrum Analyzer Basics www.agilent.com/find/backtobasics
Slide 21
Frequency accuracy is often listed under the Frequency Readout Accuracy specification and is usually specified as the
sum of several sources of errors, including frequency-reference inaccuracy, span error, and RBW center-frequency error.
Frequency-reference accuracy is determined by the basic architecture of the analyzer. The quality of the instrument's
internal timebase is also a factor, however, many spectrum analyzers use an ovenized, high-performance crystal
oscillator as a standard or optional component, so this term is small.
There are two major design categories of modern spectrum analyzers: synthesized and free-running. In a synthesized
analyzer, some or all of the oscillators are phase-locked to a single, traceable, reference oscillator. These analyzers
have typical accuracy's on the order of a few hundred hertz. This design method provides the ultimate in performance
with according complexity and cost. Spectrum analyzers employing a free-running architecture use a simpler design
and offer moderate frequency accuracy at an economical price. Free-running analyzers offer typical accuracy's of a few
megahertz. This may not be a hindrance in many cases. For example, many times we are measuring an isolated signal,
or we need just enough accuracy to be able to identify the signal of interest among other signals.
Span error is often split into two specs, based on the fact that many spectrum analyzers are fully synthesized for small
spans, but are open-loop tuned for larger spans. (The slide shows only one span specification.)
RBW error can be appreciable in some spectrum analyzers, especially for larger RBW settings, but in most cases it is
much smaller than the span error.
3-21
Specifications
Accuracy: Frequency Readout Accuracy Example
Single Marker Example:
2 GHz
400 kHz span
3 kHz RBW
Calculation: (2x10 9Hz) x (1.3x10 -7 /yr.ref.error) = 260 Hz
1% of 400 kHz span = 4000 Hz
15% of 3 kHz RBW = 450 Hz
10 Hz residual error = 10 Hz
Total = +
_ 4720 Hz
Spectrum Analyzer Basics www.agilent.com/find/backtobasics
Slide 22
Let's use the previous equation in an example to illustrate how you can calculate the frequency
accuracy of your measurement.
If we're measuring a signal at 2 GHz, using a 400 kHz span and a 3 kHz RBW, we can determine our
frequency accuracy as follows:
Frequency reference accuracy is calculated by adding up the sources of error shown (all of which can
be found on the datasheet):
freq ref accuracy = 1.0 x 10-7 (aging) + 0.1 x 10-7 (temp stability) + 0.1 x 10-7 (setability)
+ 0.1 x 10-7 (15 warm-up) = 1.3 x 10-7/yr. ref error
Therefore, our frequency accuracy is:
(2 x 109 Hz) x (1.3 x 10-7/yr) = 260 Hz
1% of 400 kHz span = 4000 Hz
15% of 3 kHz RBW = 450 Hz
10 Hz residual error = 10 Hz
________
Total = 4720 Hz
3-22
Specifications
Accuracy: Relative Amplitude Accuracy
Display fidelity Relative
Amplitude
Frequency response
in dB
RF Input attenuator
Reference level
Resolution bandwidth
Display scaling
Spectrum Analyzer Basics www.agilent.com/find/backtobasics
Slide 23
Let's now discuss amplitude accuracy.
Most spectrum analyzers are specified in terms of both absolute and relative amplitude accuracy. Since the relative
performance of the analyzer affects both types of accuracy, we will discuss this first.
When we make relative measurements on an incoming signal, we use some part of the signal as a reference. For
example, when we make second-harmonic distortion measurements, we use the fundamental of the signal as our
reference. Absolute values do not come into play; we are interested only in how the second harmonic differs in
amplitude from the fundamental.
Relative amplitude accuracy depends upon such items as shown above. Display fidelity and frequency response will
directly affect the amplitude accuracy. The other four items, on the other hand, involve control changes made during
the course of a measurement, and therefore affect accuracy only when changed. In other words, if only the frequency
control is changed when making the relative measurement, these four uncertainties drop out. If they are changed,
however, their uncertainties will further degrade accuracy.
3-23
Specifications
Accuracy: Relative Amplitude Accuracy- Display Fidelity
Applies when signals are not placed at the same
reference amplitude Relative
Amplitude
in dB
Display fidelity includes
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