Spectrum Analyzer

Spectrum Analyzer

Our Bandwidth !

Peeping In ! •

Meet the spectrum : A spectrum in the practical sense is a collection of sine waves , when combined properly produces the required time domain signal. • The frequency domain also has its measurement strengths. • The frequency domain is better for determining the harmonic content of a signal. Amplitude (power)

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uen q e r f

tim

Time domain Measurements

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Frequency Domain Measurements

Know our friend •

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A spectrum analyzer is a device used to examine the spectral composition of some electrical, acoustic, or optical waveform. Mostly it finds application in measurement of power spectrum .

Mr.Analog & Digital – as usual! •

An analog spectrum analyzer uses either a variable bandpass filter whose mid-frequency is automatically tuned (shifted, swept) through the range of frequencies of which the spectrum is to be measured or a superheterodyne receiver where the local oscillator is swept through a range of frequencies.

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A digital spectrum analyzer computes the Fast Fourier transform (FFT), a mathematical process that transforms a waveform into the components of its frequency spectrum

Spectrum Analysis •

In various field operations involving signals there is need to ascertain the nature of the signal at several points. • Signal characteristics affect the parameters of operation of a system. • Spectrum analysis mostly involves study of the signal entering a system or that produced by it . • 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.

What’s there for me! •

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

When accuracy speaks •

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.

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There is a trade-off between how quickly the display can be updated and the frequency resolution, which is for example relevant for distinguishing frequency components that are close together.

The basic types •

FFT Spectrum Analyzer

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.

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Swept Spectrum Analyzer

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.

A

Parallel filters measured simultaneously

f1 f2 Filter 'sweeps' over range of interest

f

FFT Spectrum Analyzer THE MEASUREMENT SYSTEM •

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.

The game of sampling! • • • •

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The rate at which points are taken by the sampler is a very important parameter of the FFT analyzer. In order for an analog waveform to be represented correctly with discrete values, it must be sampled at a sufficiently high rate. According to the sampling theorem, a signal must be sampled at a rate of twice the highest frequency component (the Nyquist rate). Any component whose frequency is higher than the Nyquist rate will appear in the measurement as a lower frequency component. This phenomenon is called aliasing. To avoid aliasing, an analog low-pass filter is placed at the input before the sampler. The low-pass filter determines the highest frequency of the FFT analyzer.

Role of LPF

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The rate at which signals can be represented without error is one half the maximum sampling rate. Signals are often cut off at a lower frequency to provide sampling rates greater than twice the maximum frequency components. Typically the cutoff of the low-pass filter is 2.5 times less than the maximum sampling rate of the analyzer. This determines the maximum frequency component.

Operation • • • •

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If the number of samples is kept equal as the frequency range increases, the spacing between frequency bins increases. Thus the frequency resolution decreases. An alternative is to increase the number of samples acquired. This will increase the rate of sampling . If the time to compute the FFT was faster than the rate at which the data was sampled, then an FFT could be performed for each point. A shortcut is to take a certain number of samples and transfer them to an intermediate buffer. The FFT takes the data from this buffer to perform its operation. If the FFT is computed before the next time record is placed in the buffer, then the analyzer is running in real time.

Observations •

The number of samples in the time record is inversely proportional to the frequency span. It takes less time to compute the FFT for larger frequency spans. • The point at which the frequency span time record equals the time it takes to compute the FFT is called the real-time bandwidth. GEARING UP !! • 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 . • Another method used by computer-based instruments is to use a digitizer to acquire the data, then transfer the data to a memory buffer. The FFT is then performed on the host PC in software.

Swept Spectrum Analyzer •

Very basically, these analyzers "sweep" across the frequency range of interest, displaying all the frequency components present. • 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.

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It has 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.

OPERATION • • • • • •

A voltage-controlled oscillator (VCO) sweeps through a range of frequencies that are mixed with the incoming signal. The signal from the input and the signal from the VCO are passed through a mixer. A mixer is a nonlinear device that produces the sum and difference of the original signal and the signal from the VCO, as well as the original signals and their harmonics. An intermediate frequency (IF) filter extracts the desired sum or difference of the original signals. The detector produces a voltage level relative to the amount of power received from the incoming signal. As the VCO sweeps different frequencies, the detector produces a corresponding voltage level, or power measurement.

OBSERVATIONS • • • • • • •

An important parameter of the swept analyzer is resolution bandwidth. It is determined by the IF filter portion below the minimum insertion-loss point. Often the IF filter section is composed of a number of filters, which together determine the resolution bandwidth. Resolution bandwidth is affected by the speed at which the instrument sweeps the frequency range. The IF filter requires a certain time to respond to signals placed at the input, so the analyzer cannot sweep through the frequency range too fast. Two errors can result from sweeping through the frequency range too quickly. First, the amplitude is at a lower level than if it were swept at a slower speed. Second, the signal shifts up in frequency.

Swept •

FFT

One of the principal advantages that the swept analyzer has over the FFT analyzer is its frequency range. Because the FFT analyzer needs to acquire a digital time domain waveform, the frequency range of the FFT analyzer is dependent on the sampling rate of the ADC. • The sampling rate of the analyzer determines the highest frequency that can be analyzed with the FFT. Current ADC technology has brought sampling rates into the MHz range. Swept spectrum analyzers, on the other hand, can measure frequencies in the high GHz range. • A key advantage of the FFT analyzer over the swept spectrum analyzer is its speed. Because the sweep rate is proportional to the resolution bandwidth squared, the sweep rate is decreased for smaller resolution bandwidths. This increases the total measurement time. • The FFT analyzer is only limited in time by how long it takes to acquire the data and to compute the FFT.

Advice time !!! •It is important to consider how the properties of each instrument will affect the measurements when choosing an instrument for high-frequency spectrum analysis. • Making high-frequency measurements requires an instrument that has an appropriate frequency range for the signal. FFT analyzers have a lower frequency range than swept spectrum analyzers, making swept analyzers the better choice for very high-frequency ranges. •If the length of measurement time is critical, such as with transient analysis, then the FFT analyzer is the better choice because of its speed. Because the swept spectrum analyzer does not provide phase information, the FFT analyzer must be selected if this information is

The ‘BIG’ Vector ! •

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Vector signal analyzers ( VSAs) also digitize the time domain signal like Fourier analyzers, but extend the capabilities to the RF frequency range . They are especially useful for characterizing complex signals such as burst, transient or modulated signals used in communications, video, broadcast, sonar, and ultrasound imaging applications.

The Agilent 89650s

Perform complete RF and modulation analysis from 3 Hz to 26.5 GHz with 80MHz of analysis bandwidth and 75 dB (typical) of dynamic range using the 89650S vector signal analysis bundle.

Theory of Operation Spectrum Analyzer Block Diagram RF input attenuato r

IF gain

IF filter

detecto r

mixer

Input signal Log Amp

Pre-Selector Or Low Pass Filter

local oscillator

Crystal Reference

vide o filter

sweep generato r CRT display

We make him work ! •

The major components in a spectrum analyzer are the

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RF input attenuator, mixer, IF (Intermediate Frequency) gain, • IF filter, detector, • video filter, • local oscillator, • sweep generator • CRT display.

Theory of Operation Mixer

MIXER

inpu t

RF f sig

IF LO

f LO

f LO+ f sig

f LO- f sig f sig

f LO

MIXER • •

A mixer is a device that converts a signal from one frequency to another. It is sometimes called a frequency-translation device.

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A mixer is a non-linear device (frequencies are present at the output that were not present at the input).

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The output of a mixer consists of the two original signals (fsig and fLO) as well as the sum (fLO+fsig) and difference (fLO-fsig) frequencies of these two signals.

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In a spectrum analyzer, the difference frequency is actually the frequency of interest. The mixer has converted our RF input signal to an IF (Intermediate Frequency) signal that the analyzer can now filter, amplify and detect for the purpose of displaying the signal on the screen.

Theory of Operation IF Filter

Input Spectru m IF Bandwidth (RBW) Displa y

IF FILTER

IF FILTER •

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 a broad range of variable resolution bandwidth settings , the instrument can be optimized for the sweep and signal conditions, letting trade-off frequency selectivity (the ability to resolve signals), signal-tonoise ratio (SNR), and measurement speed. •

As RBW is narrowed, selectivity is improved (we are able to resolve the two input signals). This will also often improve SNR.

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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.

Theory of Operation Detector

DETECTOR

amplitud e

"bins "

Positive detection: largest value in bin displayed Negative detection: smallest value in bin displayed Sample detection: last value in bin displayed

DETECTOR •

The analyzer must convert the IF signal to a baseband or video signal so it can be viewed on the instrument's display. This is accomplished with an envelope detector which then deflects the CRT beam on the y-axis, or amplitude axis.

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Many modern spectrum analyzers have digital displays which first digitize the video signal with an analog-to-digital converter (ADC). This allows for several different detector modes that dramatically effect how the signal is displayed.

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The positive-peak detector mode captures and displays the peak value of the signal over the duration of one trace element. This mode is good for analyzing sinusoids, but tends to over-respond to noise when no sinusoids are present. • The negative-peak detector mode captures the minimum value of the signal for each bin.

Continued... •

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In sample detection mode, a random value for each "bin" of data (also called a trace element) is produced. This detector mode is best for computing the rms value of noise or noise-like signals, but it may miss the peaks of burst signals and narrowband signals when the RBW is narrower than the frequency spacing of the bins.

For displaying both signals and noise, a detector mode called the normal detector mode (or sometimes the rosenfell detector) is used. • In this mode, if the video signal is monotonically increasing or decreasing during the period representing one trace element, then it is assumed that a spectral component is being measured, and positive-peak detection is used. • When a minimum value is displayed, the maximum value is saved and compared to the maximum value for the next trace element. The higher of the two values is displayed. This technique provides a better visual display of random noise than peak-detection yet avoids the missed-signal problem of sample-detection.

Theory of Operation Video Filter VIDEO FILTER

VIDEO AMPLIFIER • 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.

Theory of Operation Other Components

LO SWEEP GEN RF INPUT ATTENUATOR

frequenc y CRT DISPLAY IF GAIN

THE AUXILLARIES •

The local oscillator is 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. •

This also deflects the CRT beam horizontally across the screen from left to right, creating the frequency domain in the x-axis.

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The RF input attenuator is a step attenuator located between the input connector and the first mixer. It is also called the RF attenuator.

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This is used to adjust the level of the signal incident upon the first mixer.

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This is important in order to prevent mixer gain compression and distortion due to high-level and/or broadband signals.

Continued... •

The IF gain is located after the mixer but before the IF, or RBW, filter.

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This is used to adjust the vertical position of signals on the display without affecting the signal level at the input mixer.

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When changed, the value of the reference level is changed accordingly.

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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.

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The IF gain will automatically be changed to compensate for input attenuator changes, so signals remain stationary on the CRT display, and the reference level is not changed.

Theory of Operation How it all works together fs 0

1

2

3 (GHz)

mixer

LO Range f LO

Signal Range f LO- f s

f LO+f s

fs 0

IF filter 1

input

fs 2

3

4 3. 6

sweep generator

5

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detecto r

6. 5 3. 6 f IF A

LO

f LO

0 4

3 3. 6

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(GHz) 6. 5

1

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3 (GHz) f

CRT display

Get

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set

GO!

First of all, the signal to be analyzed is connected to the input of the spectrum analyzer. This input signal is then combined with the LO through the mixer, to convert (or translate) it to an intermediate frequency (IF). These signals are then sent to the IF filter. The output of this filter is detected, indicating the presence of a signal component at the analyzer's tuned frequency. The output voltage of the detector is used to drive the vertical axis (amplitude) of the analyzer display. The sweep generator provides synchronization between the horizontal axis of the display (frequency) and tuning of the LO. The resulting display shows amplitude versus frequency of spectral components of each incoming signal. The horizontal arrows are intended to illustrate the "sweeping" of the analyzer. Starting with LO at 3.6 GHz, the output of the mixer has four signals, one of which is at 3.6 GHz (fLO).

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IF filter is also at 3.6 GHz (it's shape has been imposed onto the frequency graph for clarity). Therefore, we expect to see this signal on the display. At 0 Hz on the CRT, we do indeed see a signal - this is called "LO Feedthrough". • Sweep generator moving to the right, causes the LO to sweep upward in frequency. As the LO sweeps, so too will three of the mixer output signals (the input signal is stationary). • As the LO Feedthrough moves out of the IF filter bandwidth, we see it taper off on the display. As soon as the difference frequency (fLO-fs) comes into the skirt of the IF filter, we start to see it. • When it is at the center (e.g. 3.6 GHz) we see the full amplitude of this signal on the display. • And, as it moves further to the right, it leaves the filter skirt, and no signal is seen on the display. • The signal is being swept through the fixed IF filter, and properly displayed on the analyzer screen.

That's how it works!

Theory of Operation Front Panel Operation

Softkey s

Primary functions (Frequency, Amplitude, Span)

8563A

SPECTRUM ANALYZER

9 kHz - 26.5 GHz

Control functions (RBW, sweep time, VBW) RF Input

Numeri c

Buttons ! •

The three primary hardkeys on any spectrum analyzer are: frequency, amplitude, and span. • 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.

More controls • Modern analyzers have both hardkeys and softkeys (next to the CRT display). • The softkeys allow to access several different functions/features under one hardkey. • For example, there will typically be a hardkey labeled "BW", which when pressed gives the choice of changing either the RBW or the VBW depending upon which softkey you press. • Most analyzers allow 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.

Filters – the technical heroes •

Resolving signals After the IF gain amplifier, the IF section which consists of the analog and/ or digital resolution bandwidth ( RBW) filters appears . • Analog filters Frequency resolution is the ability of a spectrum analyzer to separate two input sinusoids into distinct responses. •

A sine wave signal only has energy at one frequency, so we shouldn't have any resolution problems. • Two signals, no matter how close in frequency, should appear as two lines on the display • The output of a mixer includes the sum and difference products plus the two original signals (input and LO). • A bandpass filter determines the intermediate frequency, and this filter selects the desired mixing product and rejects all other signals.

Contd.. • Since the input signal is fixed and the local oscillator is swept, the products from the mixer are also swept. • If a mixing product happens to sweep past the IF, the characteristic shape of the bandpass filter is traced on the display. • The narrowest filter in the chain determines the overall displayed bandwidth

Digital filters •

Some spectrum analyzers use digital techniques to realize their resolution bandwidth filters. Digital filters can provide important benefits, such as dramatically improved bandwidth selectivity. The Agilent PSA Series spectrum analyzers implement all resolution bandwidths digitally. Other analyzers, such as the Agilent ESA-E Series, take a hybrid approach, using analog filters for the wider bandwidths and digital filters for bandwidths of 300 Hz and below.

Spectral leakage