Spectrum Analyzer

Display frequency spectrum

• Library:

• DSP System Toolbox / Sinks

  DSP System Toolbox HDL Support / Sinks

• 

Description

The Spectrum Analyzer block, referred to here as the scope, displays the frequency spectra of signals.

You can use the Spectrum Analyzer block in models running in Normal or Accelerator simulation modes. You can also use the Spectrum Analyzer block in models running in Rapid Accelerator or External simulation modes, with some limitations.

You can use the Spectrum Analyzer block inside all subsystems and conditional subsystems. Conditional subsystems include enabled subsystems, triggered subsystems, enabled and triggered subsystems, and function-call subsystems. See Conditionally Executed Subsystems Overview (Simulink) for more information.

Measurements

• Cursors — Measure signal values using vertical and horizontal cursors.

• Peak Finder — Find maxima, showing the x-axis values at which they occur.

• Channel Measurements — Measure the occupied bandwidth or adjacent channel power ratio (ACPR).

• Distortion Measurements — Measure harmonic distortion and intermodulation distortion.

• CCDF Measurements — Measure the complimentary cumulative distribution function. CCDF measurements show the probability of a signal’s instantaneous power being a specified level above the signal’s average power.

• Spectral Masks — Visualize spectrum limits and compare spectrum values to specification values.

Programmatic Control

You can configure and display Spectrum Analyzer settings from the command line with the SpectrumAnalyzerConfiguration object.

Ports

Input

Port_1 — Signals to visualize

scalar | vector | matrix | array

Connect the signals you want to visualize. You can have up to 96 input ports. Input signals can have these characteristics:

• Signal Domain — Frequency or time signals

• Type — Discrete (sample-based and frame-based).

• Data type — Any data type that Simulink^® supports. See Data Types Supported by Simulink (Simulink).

• Dimension — One dimensional (vector), two dimensional (matrix), or multidimensional (array). Input must have fixed number of channels. See Signal Dimensions (Simulink) and Determine Signal Dimensions (Simulink).

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64 | fixed point
Complex Number Support: Yes

Parameters

Spectrum Settings

The Spectrum Settings pane appears at the right side of the Spectrum Analyzer window. These settings control how the spectrum is calculated. To show the Spectrum Settings, in the Spectrum Analyzer menu, select View > Spectrum Settings or use the button in the toolbar.

Main options

Input domain — Domain of the input signal

Time (default) | Frequency

The domain of the input signal you want to visualize. If you visualize time-domain signals, the signal is transformed to the frequency spectrum based on the algorithm specified by the Method parameter.

Programmatic Use

See InputDomain.

Type — Type of spectrum to display

Power (default) | Power density | RMS

Power — Spectrum Analyzer shows the power spectrum.

Power density — Spectrum Analyzer shows the power spectral density. The power spectral density is the magnitude of the spectrum normalized to a bandwidth of 1 hertz.

RMS — Spectrum Analyzer shows the root mean squared spectrum.

Tunable: Yes

Dependency

To use this parameter, set Input domain to Time.

Programmatic Use

See SpectrumType.

View — Spectrum view

Spectrum (default) | Spectrogram | Spectrum and spectrogram

Spectrum — Spectrum Analyzer shows the spectrum.

Spectrogram — Spectrum Analyzer shows the spectrogram, which displays frequency content over time. The most recent spectrogram update is at the bottom of the display, and time scrolls from the bottom to the top of the display.

Spectrum and spectrogram — Spectrum Analyzer shows both the spectrum and spectrogram.

Tunable: Yes

Programmatic Use

See ViewType.

Sample rate — Sample rate of the input signal in hertz

Inherited (default) | positive scalar

Sample rate of the input signal in hertz, specified as either

• Inherited to use the same sample rate as the input signal.

• Positive scalar. The specified sample rate must be at least twice the input signal sample rate. Otherwise, you might see unexpected behavior in your signal visualization due to aliasing.

Programmatic Use

See SampleRate.

Method — Spectrum estimation method

Filter Bank (default) | Welch

Select Welch or Filter Bank as the spectrum estimation method. For more details about the two spectrum estimation algorithms, see Algorithms.

Tunable: No

Dependency

To use this parameter, set Input domain to Time.

Programmatic Use

See Method.

Full frequency span — Use entire Nyquist frequency interval

on (default) | off

Select this check box to compute and plot the spectrum over the entire Nyquist frequency interval.

Tunable: Yes

Dependency

To use this parameter, set Input domain to Time.

Programmatic Use

See FrequencySpan.

Span (Hz) — Frequency span in hertz

10e3 (default) | real positive scalar

Specify the frequency span in hertz. Use this parameter with the CF (Hz) parameter to define the frequency span around a center frequency. This parameter defines the range of values shown on the Frequency axis in the Spectrum Analyzer window.

Tunable: Yes

Dependencies

To use this parameter, you must:

• Set Input domain to Time.

• Clear the Full frequency span check box.

• Set the Span (Hz)/Fstart (Hz) drop-down to Span (Hz).

Programmatic Use

See FrequencySpan and Span.

CF (Hz) — Center frequency in hertz

0 (default) | scalar

Specify the center frequency, in hertz. Use this parameter with the Span (Hz) parameter to define the frequency span around a center frequency. This parameter defines the value shown at the middle point of the Frequency axis on the Spectrum Analyzer window.

Tunable: Yes

Dependencies

To use this parameter, you must:

• Set Input domain to Time.

• Clear the Full frequency span check box.

• Set the Span (Hz)/Fstart (Hz) drop-down to Span (Hz).

Programmatic Use

See CenterFrequency.

FStart (Hz) — Start frequency in hertz

-5e3 (default) | scalar

Specify the start frequency in hertz. Use this parameter with the FStop (Hz) parameter to define the range of frequency-axis values using start frequency and stop frequency. This parameter defines the value shown at the leftmost side of the Frequency axis on the Spectrum Analyzer window.

Tunable: Yes

Dependencies

To use this parameter, you must:

• Set Input domain to Time.

• Clear the Full frequency span check box.

• Set the Span (Hz)/FStart (Hz) drop-down to FStart (Hz).

Programmatic Use

See StartFrequency.

FStop (Hz) — Stop frequency in hertz

5e3 (default) | scalar

Specify the stop frequency, in hertz. Use this parameter with the FStart (Hz) parameter to define the range of Frequency axis values. This parameter defines the value shown at the rightmost side of the Frequency axis on the Spectrum Analyzer window.

Tunable: Yes

Dependencies

To use this parameter, you must:

• Set Input domain to Time.

• Clear the Full frequency span check box.

• Set the Span (Hz)/FStart (Hz) drop-down to FStart (Hz).

Programmatic Use

See StopFrequency.

Frequency (Hz) — Frequency vector

Auto (default) | Input port | monotonically increasing vector

Set the frequency vector which determines the x-axis of the display.

• Auto — The frequency vector is calculated from the length of the input. See Frequency Vector.

• Input port — When selected, an input port appears on the block for the frequency vector input.

• Custom vector — Enter a custom vector as the frequency vector. The length of the custom vector must be equal to the frame size of the input signal.

Tunable: No

Dependency

To use this parameter, set Input domain to Frequency.

Programmatic Use

See FrequencyVector.

RBW (Hz) — Resolution bandwidth

Auto (default) | Input port | positive scalar

The resolution bandwidth in hertz. This parameter defines the smallest positive frequency that can be resolved. By default, this parameter is set to Auto. In this case, the Spectrum Analyzer determines the appropriate value to ensure that there are 1024 RBW intervals over the specified frequency span.

If you set this parameter to a numeric value, the value must allow at least two RBW intervals over the specified frequency span. In other words, the ratio of the overall frequency span to RBW must be greater than two:

$$\frac{span}{RBW}>2$$

For frequency input only, you can use an input port to set the RBW value.

Tunable: Yes

Dependency

To use this parameter, set either:

• Input domain to Time and the RBW (Hz)/Window length/Number of frequency bands drop-down to RBW (Hz).

• Input domain to Frequency.

Programmatic Use

See RBW.

Input units — Units of frequency input

Auto (default) | dBm | dBV | dBW | Vrms | Watts

Select the units of the frequency-domain input. This property allows the Spectrum Analyzer to scale frequency data if you choose a different display unit with the Units property.

Tunable: No

Dependency

This option is only available when Input domain is set to Frequency.

Programmatic Use

See InputUnits.

Window length — Length of window in samples

1024 (default) | integer greater than 2

The length of the window, in samples. The window length used to control the frequency resolution and compute the spectral estimates. The window length must be an integer greater than 2.

Dependencies

To use this parameter, set:

• Method to Welch

• Set the RBW (Hz)/Window length/Number of frequency bands drop-down to Window Length

Dependency

To use this parameter, set Input domain to Time.

Programmatic Use

See WindowLength.

Number of frequency bands — FFT length

Auto (default) | positive integer

Specify the fast Fourier transform (FFT) length to control the number of frequency bands. If the value is Auto, the Spectrum Analyzer uses the entire frame size to estimate the spectrum. If you specify the number of frequency bands, you set the input buffer size.

Dependencies

To use this parameter, set:

• Method to Filter Bank

• Set the RBW (Hz)/Window length/Number of frequency bands drop-down to Number of frequency bands

Programmatic Use

See FFTLength

Taps per band — Number of filter taps

12 (default) | positive even integer

Specify the number of filter taps or coefficients for each frequency band. This number must be a positive even integer. This value corresponds to the number of filter coefficients per polyphase branch. The total number of filter coefficients is equal to Taps Per Band + FFT Length.

Dependency

To use this parameter, you must set the RBW (Hz)/Window length/Number of frequency bands drop-down to Number of frequency bands.

Programmatic Use

See NumTapsPerBand.

NFFT — Number of FFT points

Auto (default) | positive integer

Specify the length of the FFT that Spectrum Analyzer uses to compute spectral estimates. Acceptable options are Auto or a positive integer.

The NFFT value must be greater than or equal to the value of the Window length parameter. By default, when NFFT is set to Auto, the Spectrum Analyzer sets NFFT equal to the value of Window length. When in RBW mode, the specified RBW value is used to calculate an FFT length that equals the window length.

When this parameter is set to a positive integer, this parameter is equivalent to the n parameter of the fft function.

Dependencies

To use this parameter, you must set the RBW (Hz)/Window length/Number of frequency bands drop-down to Window length.

Programmatic Use

See FFTLength.

Samples/update — Required number of input samples

positive scalar

This property is read-only.

The number of input samples required to compute one spectral update. You cannot modify this parameter; it is shown in the spectrum analyzer for informational purposes only. This parameter is directly related to RBW (Hz)/Window length/Number of frequency bands. For more details, see Algorithms.

If the input does not have enough samples to achieve the resolution bandwidth that you specify, Spectrum Analyzer produces a message on the display.

Spectrogram Settings

Channel — Spectrogram channel

channel name

Select the signal channel for which the spectrogram settings apply.

Dependencies

To use this option, set View to Spectrogram or Spectrum and spectrogram.

Programmatic Use

See SpectrogramChannel.

Time res. (s) — Time resolution in seconds

Auto (default) | positive number

Time resolution is the amount of data, in seconds, used to compute a spectrogram line. The minimum attainable resolution is the amount of time it takes to compute a single spectral estimate. The tooltip displays the minimum attainable resolution given the current settings.

The time resolution value is determined based on frequency resolution method, the RBW setting, and the time resolution setting.

Method	Frequency Resolution Method	Frequency Resolution Setting	Time Resolution Setting	Resulting Time Resolution in Seconds
Welch or Filter Bank	RBW (Hz)	Auto	Auto	1/RBW
Welch or Filter Bank	RBW (Hz)	Auto	Manually entered	Time Resolution
Welch or Filter Bank	RBW (Hz)	Manually entered	Auto	1/RBW
Welch or Filter Bank	RBW (Hz)	Manually entered	Manually entered	Must be equal to or greater than the minimum attainable time resolution, 1/RBW. Several spectral estimates are combined into one spectrogram line to obtain the desired time resolution. Interpolation is used to obtain time resolution values that are not integer multiples of 1/RBW.
Welch	Window length	—	Auto	1/RBW
Welch	Window length	—	Manually entered	Must be equal to or greater than the minimum attainable time resolution. Several spectral estimates are combined into one spectrogram line to obtain the desired time resolution. Interpolation is used to obtain time resolution values that are not integer multiples of 1/RBW.
Filter Bank	Number of frequency bands	—	Auto	1/RBW
Filter Bank	Number of frequency bands	—	Manually entered	Must be equal to or greater than the minimum attainable time resolution, 1/RBW.

Tunable: Yes

Dependency

To use this option, set View to Spectrogram or Spectrum and spectrogram.

Programmatic Use

See TimeResolution.

Time span — Time span in seconds

Auto (default) | positive scalar

The time span over which the Spectrum Analyzer displays the spectrogram specified in seconds. The time span is the product of the desired number of spectral lines and the time resolution. The tooltip displays the minimum allowable time span, given the current settings. If the time span is set to Auto, 100 spectral lines are used.

Tunable: Yes

Dependency

To use this option, set View to Spectrogram or Spectrum and spectrogram.

Programmatic Use

See TimeSpan.

Window Options

Overlap (%) — Segment overlap percentage

0 (default) | scalar between 0 and 100

This parameter defines the amount of overlap between the previous and current buffered data segments. The overlap creates a window segment that is used to compute a spectral estimate. The value must be greater than or equal to zero and less than 100.

Tunable: Yes

Programmatic Use

See OverlapPercent.

Window — Windowing method

Hann (default) | Rectangular | Blackman-Harris | Chebyshev | Flat Top | Hamming | Kaiser | custom window function name

The windowing method to apply to the spectrum. Windowing is used to control the effect of sidelobes in spectral estimation. The window you specify affects the window length required to achieve a resolution bandwidth and the required number of samples per update. For more information about windowing, see Windows.

Tunable: Yes

Programmatic Use

See Window.

Attenuation — Sidelobe attenuation

60 (default) | scalar greater than or equal to 45

The sidelobe attenuation in decibels (dB). The value must be greater than or equal to 45.

Dependency

This parameter applies only when you set the Window parameter to Chebyshev or Kaiser.

Programmatic Use

See SidelobeAttenuation.

NENBW — Normalized effective noise bandwidth

scalar

This property is read-only.

The normalized effective noise bandwidth of the window. You cannot modify this parameter; it is shown for informational purposes only. This parameter is a measure of the noise performance of the window. The value is the width of a rectangular filter that accumulates the same noise power with the same peak power gain.

The rectangular window has the smallest NENBW, with a value of 1. All other windows have a larger NENBW value. For example, the Hann window has an NENBW value of approximately 1.5.

Trace Options

Units — Spectrum units

dBm (default) | dBW | Watts | Vrms | dBV | dBFS

The units of the spectrum. The available values depend on the value of the Type parameter.

Tunable: Yes

Programmatic Use

See SpectrumUnits.

Full scale — Full scale for dBFS units

Auto (default) | positive real scalar

The full scale used for the decibel full scale (dBFS) units. By default, the Spectrum Analyzer uses the entire spectrum scale. Specify a positive real scalar for the dBFS full scale.

Tunable: Yes

Dependencies

To enable this parameter, set:

• Input domain to Time

• Units to dBFS

Programmatic Use

See FullScale.

Averaging method — Smoothing method

Exponential (default) | Running

Specify the smoothing method as:

• Exponential — Weighted average of samples. Use the Forgetting factor property to specify the weighted forgetting factor.

• Running — Running average of the last n samples. Use the Averages property to specify n.

For more information about the averaging methods, see Averaging Method.

Programmatic Use

See AveragingMethod.

Averages — Number of spectral averages

1 (default) | positive integer

Specify the number of spectral averages as a positive integer. The spectrum analyzer computes the current power spectrum estimate by computing a running average of the last N power spectrum estimates. This parameter defines the number of spectral averages, N.

Dependencies

This parameter applies only when:

• View is Spectrum or Spectrum and spectrogram.

• Averaging method is Running.

Programmatic Use

See SpectralAverages.

Forgetting factor — Weighting forgetting factor

0.9 (default) | scalar in the range (0,1]

Specify the exponential weighting as a scalar value greater than 0 and less than or equal to 1.

Dependency

This parameter applies only when the Averaging method is Exponential.

Programmatic Use

See ForgettingFactor.

Reference load — Reference load

1 (default) | positive real scalar

The reference load in ohms that the Spectrum Analyzer uses as a reference to compute power values.

Programmatic Use

See ReferenceLoad.

Scale — Scale of frequency axis

Linear (default) | Logarithmic

Choose a linear or logarithm scale for the frequency axis. When the frequency span contains negative frequency values, you cannot choose the logarithmic option.

Programmatic Use

See FrequencyScale.

Offset — Constant frequency offset

0 (default) | scalar

The constant frequency offset to apply to the entire spectrum, or a vector of frequencies to apply to each spectrum for multiple inputs. The offset parameter is added to the values on the Frequency axis in the Spectrum Analyzer window. This parameter is not used in any spectral computations. You must take the parameter into consideration when you set the Span (Hz) and CF (Hz) parameters to ensure that the frequency span is within the Nyquist frequency interval.

Dependency

To use this parameter, set Input domain to Time.

Programmatic Use

See FrequencyOffset.

Normal trace — Normal trace view

on (default) | off

When this check box is selected, the Spectrum Analyzer calculates and plots the power spectrum or power spectrum density. Spectrum Analyzer performs a smoothing operation by averaging several spectral estimates.

Dependencies

To clear this check box, you must first select either the Max hold trace or the Min hold trace parameter. This parameter applies only when View is Spectrum or Spectrum and spectrogram.

Programmatic Use

See PlotNormalTrace.

Max hold trace — Maximum hold trace view

off (default) | on

Select this check box to enable Spectrum Analyzer to plot the maximum spectral values of all the estimates obtained.

Dependency

This parameter applies only when View is Spectrum or Spectrum and spectrogram.

Programmatic Use

See PlotMaxHoldTrace.

Min hold trace — Minimum hold trace view

off (default) | on

Select this check box to enable Spectrum Analyzer to plot the minimum spectral values of all the estimates obtained.

Dependency

This parameter applies only when View is Spectrum or Spectrum and spectrogram.

Programmatic Use

See PlotMinHoldTrace.

Two-sided spectrum — Enable two-sided spectrum view

off (default) | on

Select this check box to enable a two-sided spectrum view. In this view, both negative and positive frequencies are shown. If you clear this check box, Spectrum Analyzer shows a one-sided spectrum with only positive frequencies. Spectrum Analyzer requires that this parameter is selected when the input signal is complex-valued.

Programmatic Use

See PlotAsTwoSidedSpectrum.

Configuration Properties

The Configuration Properties dialog box controls visual aspects of the Spectrum Analyzer. To open the Configuration Properties, in the Spectrum Analyzer menu, select View > Configuration Properties or select the button in the toolbar drop-down.

Title — Display title

character vector | string

Specify the display title. Enter %<SignalLabel> to use the signal labels in the Simulink model as the axes titles.

Tunable: Yes

Programmatic Use

See Title.

Show legend — Display signal legend

off (default) | on

Show signal legend. The names listed in the legend are the signal names from the model. For signals with multiple channels, a channel index is appended after the signal name. Continuous signals have straight lines before their names and discrete signals have step-shaped lines.

From the legend, you can control which signals are visible. This control is equivalent to changing the visibility in the Style parameters. In the scope legend, click a signal name to hide the signal in the scope. To show the signal, click the signal name again. To show only one signal, right-click the signal name, which hides all other signals. To show all signals, press ESC.

Note

The legend only shows the first 20 signals. Any additional signals cannot be viewed or controlled from the legend.

Dependency

To enable this parameter, set View to Spectrum or Spectrum and spectrogram.

Programmatic Use

See ShowLegend.

Show grid — Show internal grid lines

on (default) | off

Show internal grid lines on the Spectrum Analyzer

Programmatic Use

See ShowGrid.

Y-limits (minimum) — Y-axis minimum

-80 (default) | scalar

Specify the minimum value of the y-axis.

Programmatic Use

See YLimits.

Y-limits (maximum) — Y-axis maximum

20 (default) | scalar

Specify the maximum value of the y-axis.

Programmatic Use

See YLimits.

Y-label — Y-axis label

character vector | string

To display signal units, add (%<SignalUnits>) to the label. At the beginning of a simulation, Simulink replaces (%SignalUnits) with the units associated with the signals. For example, if you have a signal for velocity with units of m/s enter

Velocity (%<SignalUnits>)

Programmatic Use

See YLabel.

Color map — Spectrogram colormap

jet(256) (default) | hot(256) | bone(256) | cool(256) | copper(256) | gray(256) | parula(256) | 3-column matrix

Select the colormap for the spectrogram, or enter a three-column matrix expression for the colormap. For more information about colormaps, see colormap.

Tunable: Yes

Dependency

To use this parameter, set View to Spectrogram or Spectrum and spectrogram.

Color-limits (minimum) — Spectrogram minimum

-80 (default) | scalar

Specify the signal power for the minimum color value of the spectrogram.

Tunable: Yes

Dependency

To use this parameter, set View to Spectrogram or Spectrum and spectrogram.

Programmatic Use

See ColorLimits.

Color-limits (maximum) — Spectrogram maximum

20 (default) | scalar

Specify the signal power for the maximum color value of the spectrogram.

Tunable: Yes

Dependency

To use this parameter, set View to Spectrogram or Spectrum and spectrogram.

Programmatic Use

See ColorLimits.

Style

The Style dialog box controls how to Spectrum Analyzer appears. To open the Style properties, in the Spectrum Analyzer menu, select View > Style or select the button in the toolbar drop-down.

Figure color — Window background

gray (default) | color picker

Specify the color that you want to apply to the background of the scope figure.

Plot type — Plot type

Line (default) | Stem

Specify whether to display a Line or Stem plot.

Programmatic Use

See PlotType.

Axes colors — Axes background color

black (default) | color picker

Specify the color that you want to apply to the background of the axes.

Properties for line — Channel for visual property settings

channel names

Specify the channel for which you want to modify the visibility, line properties, and marker properties.

Visible — Channel visibility

on (default) | off

Specify whether the selected channel is visible. If you clear this check box, the line disappears. You can also change signal visibility using the scope legend.

Line — Line style

line, 0.5, yellow (default)

Specify the line style, line width, and line color for the selected channel.

Marker — Data point markers

none (default)

Specify marks for the selected channel to show at its data points. This parameter is similar to the Marker property for plots. You can choose any of the marker symbols from the drop-down.

Axes Scaling

The Axes Scaling dialog box controls the axes limits of the Spectrum Analyzer. To open the Axes Scaling properties, in the Spectrum Analyzer menu, select Tools > Axes Scaling > Axes Scaling Properties.

Axes scaling/Color scaling — Automatic axes scaling

Auto (default) | Manual | After N Updates

Specify when the scope automatically scales the y-axis. If the spectrogram is displayed, specify when the scope automatically scales the color axis. By default, this parameter is set to Auto, and the scope does not shrink the y-axis limits when scaling the axes or color. You can select one of the following options:

• Auto — The scope scales the axes or color as needed, both during and after simulation. Selecting this option shows the Do not allow Y-axis limits to shrink or Do not allow color limits to shrink.

• Manual — When you select this option, the scope does not automatically scale the axes or color. You can manually scale the axes or color in any of the following ways:

  • Select Tools > Scaling Properties.

  • Press one of the Scale Axis Limits toolbar buttons.

  • When the scope figure is the active window, press Ctrl+A.

• After N Updates — Selecting this option causes the scope to scale the axes or color after a specified number of updates. This option is useful, and most efficient, when your frequency signal values quickly reach steady-state after a short period. Selecting this option shows the Number of updates edit box where you can modify the number of updates to wait before scaling.

Tunable: Yes

Programmatic Use

See AxesScaling.

Do not allow Y-axis/color limits to shrink — Axes scaling limits

on (default) | off

When you select this parameter, the y-axis is allowed to grow during axes scaling operations. If the spectrogram is displayed, selecting this parameter allows the color limits to grow during axis scaling. If you clear this check box, the y-axis or color limits can shrink during axes scaling operations.

Dependency

This parameter appears only when you select Auto for the Axis scaling or Color scaling parameter. When you set the Axes scaling or Color scaling parameter to Manual or After N Updates, the y-axis or color limits can shrink.

Number of updates — Number of updates before scaling

10 (default) | positive number

The number of updates after which the axes scale, specified as a positive integer. If the spectrogram is displayed, this parameter specifies the number of updates after which the color axes scales.

Tunable: Yes

Dependency

This parameter appears only when you set Axes scaling/Color scaling to After N Updates.

Programmatic Use

See AxesScalingNumUpdates.

Scale limits at stop — Scale axes at stop

off (default) | on

Select this check box to scale the axes when the simulation stops. If the spectrogram is displayed, select this check box to scale the color when the simulation stops. The y-axis is always scaled. The x-axis limits are only scaled if you also select the Scale X-axis limits check box.

Data range (%) — Percent of axes

100 (default) | number in the range [1,100]

Set the percentage of the axis that the scope uses to display the data when scaling the axes. If the spectrogram is displayed, set the percentage of the power values range within the colormap. Valid values are from 1 through 100. For example, if you set this parameter to 100, the scope scales the axis limits such that your data uses the entire axis range. If you then set this parameter to 30, the scope increases the y-axis or color range such that your data uses only 30% of the axis range.

Tunable: Yes

Align — Alignment along axes

Center (default) | Bottom | Top | Left | Right

Specify where the scope aligns your data along the axis when it scales the axes. If the spectrogram is displayed, specify where the scope aligns your data along the axis when it scales the color. If you are using CCDF Measurements, the x axis is also configurable.

Tunable: Yes

Model Examples

Spectrum Analyzer Measurements

Perform measurements using the Spectrum Analyzer block. The example contains a typical setup to perform harmonic distortion measurements (THD, SNR, SINAD, SFDR), third-order intermodulation distortion measurements (TOI), and adjacent channel power ratio measurements (ACPR). The example also shows how to view time-varying spectra by using a spectrogram and automatic peak detection.

Open Script

Display Frequency Input on Spectrum Analyzer

Visualize frequency input signals with the Spectrum Analyzer block.

Open Model

Obtain Measurements Data Programmatically for Spectrum Analyzer Block

Obtain measurements data from Spectrum Analyzer block.

Open Model

High Resolution Spectral Analysis in Simulink

Perform spectral estimation in Simulink using the filter bank method, and compare the performance with the Welch's averaged modified periodogram method.

Open Model

Block Characteristics

Data Types	Boolean | double | enumerated | fixed point | integer | single
Direct Feedthrough	no
Multidimensional Signals	yes
Variable-Size Signals	yes
Zero-Crossing Detection	no

Algorithms

Spectrum Estimation — Welch's Method

When you choose the Welch method, the power spectrum estimate is averaged modified periodograms.

Given the signal input, x, the Spectrum Analyzer does the following:

1. Multiplies x by the given window and scales the result by the window power. The Spectrum Analyzer uses the RBW or the Window Length setting in the Spectrum Settings pane to determine the data window length.

2. Computes the FFT of the signal, Y, and takes the square magnitude using Z = Y.*conj(Y).

3. Computes the current power spectrum estimate by taking the moving average of the last N number of Z's, and scales the answer by the sample rate. For details on the moving average methods, see Averaging Method.

Spectrum Analyzer requires that a minimum number of samples to compute a spectral estimate. This number of input samples required to compute one spectral update is shown as Samples/update in the Main options pane. This value is directly related to resolution bandwidth, RBW, by the following equation, or to the window length, by the equation shown in step 2.

$$N_{samples}=\frac{\left(1-\frac{O_p}{100}\right)\times NENBW\times F_s}{RBW}$$

The normalized effective noise bandwidth, NENBW, is a factor that depends on the windowing method. Spectrum Analyzer shows the value of NENBW in the Window Options pane of the Spectrum Settings pane. Overlap percentage, O_p, is the value of the Overlap % parameter in the Window Options pane of the Spectrum Settings pane. F_s is the sample rate of the input signal. Spectrum Analyzer shows sample rate in the Main Options pane of the Spectrum Settings pane.

1. When in RBW (Hz) mode, the window length required to compute one spectral update, N_window, is directly related to the resolution bandwidth and normalized effective noise bandwidth:

   $$N_{window}=\frac{NENBW\times F_s}{RBW}$$

   When in Window Length mode, the window length is used as specified.

2. The number of input samples required to compute one spectral update, N_samples, is directly related to the window length and the amount of overlap by the following equation.

   $$N_{samples}=\left(1-\frac{O_p}{100}\right)N_{window}$$

   When you increase the overlap percentage, fewer new input samples are needed to compute a new spectral update. For example, if the window length is 100, then the number of input samples required to compute one spectral update is given as shown in the following table.

   Op	Nsamples
   0%	100
   50%	50
   80%	20

3. The normalized effective noise bandwidth, NENBW, is a window parameter determined by the window length, N_window, and the type of window used. If w(n) denotes the vector of N_window window coefficients, then NENBW is given by the following equation.

   $$NENBW=N_{window}\times \frac{{\displaystyle \sum _{n=1}^{N_{window}}{w}^2(n)}}{{\left[{\displaystyle \sum _{n=1}^{N_{window}}w(n)}\right]}^2}$$

4. When in RBW (Hz) mode, you can set the resolution bandwidth using the value of the RBW (Hz) parameter on the Main options pane of the Spectrum Settings pane. You must specify a value to ensure that there are at least two RBW intervals over the specified frequency span. The ratio of the overall span to RBW must be greater than two:

   $$\frac{span}{RBW}>2$$

   By default, the RBW (Hz) parameter on the Main options pane is set to Auto. In this case, the Spectrum Analyzer determines the appropriate value to ensure that there are 1024 RBW intervals over the specified frequency span. When you set RBW (Hz) to Auto, RBW is calculated as:

   $$RB{W}_{auto}=\frac{span}{1024}$$

5. When in Window Length mode, you specify N_window and the resulting RBW is:

   $$\frac{NENBW\times F_s}{N_{window}}$$

Sometimes, the number of input samples provided are not sufficient to achieve the resolution bandwidth that you specify. When this situation occurs, Spectrum Analyzer displays a message:

Spectrum Analyzer removes this message and displays a spectral estimate when enough data has been input.

Note

The number of FFT points (N_fft) is independent of the window length (N_window). You can set them to different values if N_fft is greater than or equal to N_window.

Spectrum Estimation — Filter Bank

When you choose the Filter Bank method, the Spectrum Analyzer uses an analysis filter bank to estimate the power spectrum.

The filter bank splits the broadband input signal, x(n), of sample rate fs, into multiple narrow band signals, y₀(m), y₁(m), … , y_M-1(m), of sample rate fs/M.

The variable M represents the number of frequency bands in the filter bank. When the frequency resolution method is set to NumFrequencyBands, M is equal to the value you specify for the number of frequency bands. When the frequency resolution method is set to RBW, M is equal to the number of data points that are needed to achieve the specified RBW value or 1024, whichever is larger. The number of taps per frequency band specifies the number of filter coefficients for each frequency band of the filter bank. The total number of filter coefficients is equal to number of taps per band times the number of frequency bands, M. For more information on the analysis filter bank and how it is implemented, see the More About and the Algorithm sections in dsp.Channelizer.

After the broadband input signal is split into multiple narrow bands, the Spectrum Analyzer computes the power in each narrow band using the following equation. Each Z_i value becomes the estimate of the power over that narrow frequency band.

$$Z_i=\frac{1}{L}{\displaystyle \sum _{m=0}^{L-1}{\left|y_i[m]\right|}^2}$$

L is length of the narrow band signal, y_i(m), and i = 1, 2, …, M−1.

The power values in all the narrow bands (denoted by the Z_i) form the Z vector.

$$Z=[Z_0,Z_1,Z_2,\cdots ,Z_{M-1}]$$

The current Z vector is averaged with the previous Z vectors using one of the two moving average methods: Running or Exponential weighting. The output of the averaging operation forms the spectral estimate vector. For details on the two averaging methods, see Averaging Method.

The Spectrum Analyzer uses the RBW (Hz) or the Number of frequency band property in the Spectrum Settings pane to determine the input frame length.

Spectrum Analyzer requires a minimum number of samples to compute a spectral estimate. This number of input samples required to compute one spectral update is shown as Samples/update in the Main options pane. This value is directly related to resolution bandwidth, RBW, by the following equation.

$$N_{samples}=\frac{F_s}{RBW}$$

F_s is the sample rate of the input signal. Spectrum Analyzer shows sample rate in the Main Options pane of the Spectrum Settings pane.

1. When in RBW (Hz) mode, you can set the resolution bandwidth using the value of the RBW (Hz) parameter on the Main options pane of the Spectrum Settings pane. You must specify a value to ensure that there are at least two RBW intervals over the specified frequency span. The ratio of the overall span to RBW must be greater than two:

   $$\frac{span}{RBW}>2$$

   By default, the RBW parameter on the Main options pane is set to Auto. In this case, the Spectrum Analyzer determines the appropriate value to ensure that there are 1024 RBW intervals over the specified frequency span. Thus, when you set RBW to Auto, it is calculated by the following equation.$$RB{W}_{auto}=\frac{span}{1024}$$

2. When in Number of frequency bands mode, you specify the input frame size. When the number of frequency bands is Auto, the resulting RBW is:

   $$RBW=\frac{F_s}{\text{Input Frame Size}}$$

   When the number of frequency bands is manually specified, the resulting RBW is:

   $$RBW=\frac{F_s}{FFTLength}$$

Sometimes, the number of input samples provided are not sufficient to achieve the resolution bandwidth that you specify. When this situation occurs, Spectrum Analyzer displays a message:

Spectrum Analyzer removes this message and displays a spectral estimate when enough data has been input.

Nyquist frequency interval

When the PlotAsTwoSidedSpectrum property is set to true, the interval is $$\left[-\frac{SampleRate}{2},\frac{SampleRate}{2}\right]+FrequencyOffset$$ hertz.

When the PlotAsTwoSidedSpectrum property is set to false, the interval is $$\left[0,\frac{SampleRate}{2}\right]+FrequencyOffset$$ hertz.

Periodogram and Spectrogram

Spectrum Analyzer calculates and plots the power spectrum, power spectrum density, and RMS computed by the modified Periodogram estimator. For more information about the Periodogram method, see periodogram.

Power Spectral Density — The power spectral density (PSD) is given by the following equation.

$$\mathrm{PSD}\left(f\right)=\frac{1}{P}{\displaystyle \sum _{p=1}^P\frac{{\left|{\displaystyle \sum _{n=1}^{N_{FFT}}{x}^p\left[n\right]e^{-j2\pi f(n-1)T}}\right|}^2}{F_s\times {\displaystyle \sum _{n=1}^{N_{window}}{w}^2\left[n\right]}}}$$

In this equation, x[n] is the discrete input signal. On every input signal frame, Spectrum Analyzer generates as many overlapping windows as possible, with each window denoted as x^(p)[n], and computes their periodograms. Spectrum Analyzer displays a running average of the P most current periodograms.

Power Spectrum — The power spectrum is the product of the power spectral density and the resolution bandwidth, as given by the following equation.

$$P_{spectrum}\left(f\right)=\mathrm{PSD}\left(f\right)\times RBW=\mathrm{PSD}\left(f\right)\times \frac{F_s\times NENBW}{N_{window}}=\frac{1}{P}{\displaystyle \sum _{p=1}^P\frac{{\left|{\displaystyle \sum _{n=1}^{N_{FFT}}{x}^p\left[n\right]e^{-j2\pi f(n-1)T}}\right|}^2}{{\left[{\displaystyle \sum _{n=1}^{N_{window}}w\left[n\right]}\right]}^2}}$$

Spectrogram — You can plot any power as a spectrogram. Each line of the spectrogram is one periodogram. The time resolution of each line is 1/RBW, which is the minimum attainable resolution. Achieving the resolution you want may require combining several periodograms. You then use interpolation to calculate noninteger values of 1/RBW. In the spectrogram display, time scrolls from top to bottom, so the most recent data is shown at the top of the display. The offset shows the time value at which the center of the most current spectrogram line occurred.

Frequency Vector

When set to Auto, the frequency vector for frequency-domain input is calculated by the software.

When the PlotAsTwoSidedSpectrum property is set to true, the frequency vector is:

$$\left[-\frac{SampleRate}{2},\frac{SampleRate}{2}\right]$$

When the PlotAsTwoSidedSpectrum property is set to false, the frequency vector is:

$$\left[0,\frac{SampleRate}{2}\right]$$

Occupied BW

The Occupied BW is calculated as follows.

1. Calculate the total power in the measured frequency range.

2. Determine the lower frequency value. Starting at the lowest frequency in the range and moving upward, the power distributed in each frequency is summed until this result is

   $$\frac{100-OccupiedBW\%}{2}$$

   of the total power.

3. Determine the upper frequency value. Starting at the highest frequency in the range and moving downward, the power distributed in each frequency is summed until the result reaches

   $$\frac{100-OccupiedBW\%}{2}$$

   of the total power.

4. The bandwidth between the lower and upper power frequency values is the occupied bandwidth.

5. The frequency halfway between the lower and upper frequency values is the center frequency.

Distortion Measurements

The Distortion Measurements are computed as follows.

1. Spectral content is estimated by finding peaks in the spectrum. When the algorithm detects a peak, it records the width of the peak and clears all monotonically decreasing values. That is, the algorithm treats all these values as if they belong to the peak. Using this method, all spectral content centered at DC (0 Hz) is removed from the spectrum and the amount of bandwidth cleared (W₀) is recorded.

2. The fundamental power (P₁) is determined from the remaining maximum value of the displayed spectrum. A local estimate (Fe₁) of the fundamental frequency is made by computing the central moment of the power near the peak. The bandwidth of the fundamental power content (W₁) is recorded. Then, the power from the fundamental is removed as in step 1.

3. The power and width of the higher-order harmonics (P₂, W₂, P₃, W₃, etc.) are determined in succession by examining the frequencies closest to the appropriate multiple of the local estimate (Fe₁). Any spectral content that decreases monotonically about the harmonic frequency is removed from the spectrum first before proceeding to the next harmonic.

4. Once the DC, fundamental, and harmonic content is removed from the spectrum, the power of the remaining spectrum is examined for its sum (P_remaining), peak value (P_maxspur), and median value (P_estnoise).

5. The sum of all the removed bandwidth is computed as W_sum = W₀ + W₁ + W₂ +...+ W_n.

   The sum of powers of the second and higher-order harmonics are computed as P_harmonic = P₂ + P₃ + P₄ +...+ P_n.

6. The sum of the noise power is estimated as:

   $$P_{noise}=(P_{remaining}\cdot dF+P_{est.noise}\cdot W_{sum})/RBW$$

   Where dF is the absolute difference between frequency bins, and RBW is the resolution bandwidth of the window.

7. The metrics for SNR, THD, SINAD, and SFDR are then computed from the estimates.

   $$\begin{array}{l}THD=10\cdot {\log }_{10}\left(\frac{P_{harmonic}}{P_1}\right)\\ SINAD=10\cdot {\log }_{10}\left(\frac{P_1}{P_{harmonic}+P_{noise}}\right)\\ SNR=10\cdot {\log }_{10}\left(\frac{P_1}{P_{noise}}\right)\\ SFDR=10\cdot {\log }_{10}\left(\frac{P_1}{\max \left(P_{maxspur},\max \left(P_2,P_3,\mathrm{...},P_n\right)\right)}\right)\end{array}$$

Harmonic Measurements

1. The harmonic distortion measurements use the spectrum trace shown in the display as the input to the measurements. The default Hann window setting of the Spectrum Analyzer may exhibit leakage that can completely mask the noise floor of the measured signal.

   

   The harmonic measurements attempt to correct for leakage by ignoring all frequency content that decreases monotonically away from the maximum of harmonic peaks. If the window leakage covers more than 70% of the frequency bandwidth in your spectrum, you may see a blank reading (–) reported for SNR and SINAD. If your application can tolerate the increased equivalent noise bandwidth (ENBW), consider using a Kaiser window with a high attenuation (up to 330 dB) to minimize spectral leakage.

   

2. The DC component is ignored.

3. After windowing, the width of each harmonic component masks the noise power in the neighborhood of the fundamental frequency and harmonics. To estimate the noise power in each region, Spectrum Analyzer computes the median noise level in the nonharmonic areas of the spectrum. It then extrapolates that value into each region.

4. N^th order intermodulation products occur at A*F1 + B*F2,

   where F1 and F2 are the sinusoid input frequencies and |A| + |B| = N. A and B are integer values.

5. For intermodulation measurements, the third-order intercept (TOI) point is computed as follows, where P is power in decibels of the measured power referenced to 1 milliwatt (dBm):

   • TOI_lower = P_F1 + (P_F2 - P_(2F1-F2))/2

   • TOI_upper = P_F2 + (P_F1 - P_(2F2-F1))/2

   • TOI = + (TOI_lower + TOI_upper)/2

Averaging Method

The moving average is calculated using one of the two methods:

• Running — For each frame of input, average the last N-scaled Z vectors, which are computed by the algorithm. The variable N is the value you specify for the number of spectral averages. If the algorithm does not have enough Z vectors, the algorithm uses zeros to fill the empty elements.

  

• Exponential — The moving average algorithm using the exponential weighting method updates the weights and computes the moving average recursively for each Z vector that comes in by using the following recursive equations:

  $$\begin{array}{l}{w}_N=\lambda w_{N-1}+1\\ {\overline{z}}_N=\left(1-\frac{1}{w_N}\right){\overline{z}}_{N-1}+\left(\frac{1}{w_N}\right)z_N\end{array}$$

  • λ — Forgetting factor

  • $$w_N$$ — Weighting factor applied to the current Z vector

  • $$z_N$$ — Current Z vector

  • $${\overline{z}}_{N-1}$$ — Moving average until the previous Z vector

  • $$\left(1-\frac{1}{w_N}\right){\overline{z}}_{N-1}$$ — Effect of the previous Z vectors on the average

  • $${\overline{z}}_N$$ — Moving average including the current Z vector

Extended Capabilities

C/C++ Code Generation

Generate C and C++ code using Simulink® Coder™.

This block can be used for simulation visibility in systems that generate code, but is not included in the generated code.

HDL Code Generation

Generate Verilog and VHDL code for FPGA and ASIC designs using HDL Coder™.

This block can be used for simulation visibility in subsystems that generate HDL code, but is not included in the hardware implementation.

PLC Code Generation

Generate Structured Text code using Simulink® PLC Coder™.

This block can be used for simulation visibility in systems that generate PLC code, but is not included in the generated code.

Fixed-Point Conversion

Design and simulate fixed-point systems using Fixed-Point Designer™.

This block accepts fixed-point input, but converts it to double for display.

Version History

Introduced in R2014b