Initialization

The input sine wave has two frequencies: 1000 Hz and 5000 Hz. Create two dsp.SineWave System objects to generate these two frequencies. Create a dsp.SpectrumAnalyzer System object to compute and display the power spectrum.

Fs = 44100;
Sineobject1 = dsp.SineWave('SamplesPerFrame',1024,'PhaseOffset',10,...
    'SampleRate',Fs,'Frequency',1000);
Sineobject2 = dsp.SineWave('SamplesPerFrame',1024,...
    'SampleRate',Fs,'Frequency',5000);
SA = dsp.SpectrumAnalyzer('SampleRate',Fs,'Method','Filter bank',...
    'SpectrumType','Power','PlotAsTwoSidedSpectrum',false,...
    'ChannelNames',{'Power spectrum of the input'},'YLimits',[-120 40],'ShowLegend',true);

Enable Measurements Data

To obtain the measurements, set the Enable property of the measurements to true.

SA.CursorMeasurements.Enable = true;
SA.ChannelMeasurements.Enable = true;
SA.PeakFinder.Enable = true;
SA.DistortionMeasurements.Enable = true;

Use getMeasurementsData

Stream in the noisy sine wave input signal and estimate the power spectrum of the signal using the spectrum analyzer. Measure the characteristics of the spectrum. Use the getMeasurementsData function to obtain these measurements programmatically. The isNewDataReady function indicates when there is new spectrum data. The measured data is stored in the variable data.

data = [];
for Iter = 1:1000
    Sinewave1 = Sineobject1();
    Sinewave2 = Sineobject2();
    Input = Sinewave1 + Sinewave2;
    NoisyInput = Input + 0.001*randn(1024,1);
    SA(NoisyInput);
     if SA.isNewDataReady
        data = [data;getMeasurementsData(SA)];
     end
end

The right side of the spectrum analyzer shows the enabled measurement panes. The values shown in these panes match with the values shown in the last time step of the data variable. You can access the individual fields of data to obtain the various measurements programmatically.

Compare Peak Values

Peak values are obtained by the PeakFinder property. Verify that the peak values obtained in the last time step of data match the values shown on the spectrum analyzer plot.

peakvalues = data.PeakFinder(end).Value 

peakvalues = 3×1

   26.9848
   24.1738
  -52.1809

frequencieskHz = data.PeakFinder(end).Frequency/1000

frequencieskHz = 3×1

    4.9957
    0.9905
   16.0207

Open and Inspect the Model

Filter a streaming noisy sinusoidal input signal using a Lowpass Filter block. The input signal consists of two sinusoidal tones: 1 kHz and 15 kHz. The noise is white Gaussian noise with zero mean and a variance of 0.05. The sampling frequency is 44.1 kHz. Open the model and inspect the various block settings.

model = 'spectrumanalyzer_measurements.slx';
open_system(model)

Access the configuration properties of the Spectrum Analyzer block using the get_param function.

sablock = 'spectrumanalyzer_measurements/Spectrum Analyzer';
cfg = get_param(sablock,'ScopeConfiguration');

Enable Measurements Data

To obtain the measurements, set the Enable property of the measurements to true.

cfg.CursorMeasurements.Enable = true;
cfg.ChannelMeasurements.Enable = true;
cfg.PeakFinder.Enable = true;
cfg.DistortionMeasurements.Enable = true;

Simulate the Model

Run the model. The Spectrum Analyzer block compares the original spectrum with the filtered spectrum.

sim(model)

The right side of the spectrum analyzer shows the enabled measurement panes.

Using getMeasurementsData

Use the getMeasurementsData function to obtain these measurements programmatically.

data = getMeasurementsData(cfg)

data =

  1x5 table

    SimulationTime     PeakFinder     CursorMeasurements    ChannelMeasurements    DistortionMeasurements
    ______________    ____________    __________________    ___________________    ______________________

      {[0.9985]}      [1x1 struct]       [1x1 struct]          [1x1 struct]             [1x1 struct]     

The values shown in measurement panes match the values shown in data. You can access the individual fields of data to obtain the various measurements programmatically.

Compare Peak Values

As an example, compare the peak values. Verify that the peak values obtained by data.PeakFinder match with the values seen in the Spectrum Analyzer window.

peakvalues = data.PeakFinder.Value
frequencieskHz = data.PeakFinder.Frequency/1000

peakvalues =

   26.9920
   26.2545
   -4.7240


frequencieskHz =

   15.0015
    1.0049
   11.4126

Save and Close the Model

save_system(model);
close_system(model);