This example shows how to increase the sampling rate of a signal using FIR interpolators from the DSP System Toolbox™.
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The DSP System Toolbox supports different structures to perform interpolation including FIR-based structures and CICs. Given an interpolation factor L, a common design of an FIR interpolation filter is a Nyquist filter with a cutoff frequency of pi/L and a gain of L. This type of filter leaves the original samples unchanged and interpolates L-1 samples between the original samples. See the FIRHALFBAND, FIRNYQUIST, FIREQINT and INTFILT functions as well as FDESIGN.INTERPOLATOR and FDESIGN.NYQUIST for more on the design of interpolation filters.
L = 3; % Interpolation factor Hf = fdesign.interpolator(L,'Nyquist',L); Hi = design(Hf,'SystemObject',true); % Polyphase FIR Interpolator
To interpolate by a fractional factor, you can use a Direct-Form FIR Polyphase Sample-Rate Converter. This structure uses L polyphase subfilters.
M = 2; % Decimation factor Hf = fdesign.rsrc(L,M,'Nyquist',max(L,M)); Hd2 = design(Hf,'SystemObject',true); % Polyphase FIR Fractional Decimator
The default interpolation filter has linear phase. The info analysis in the Filter Visualization Tool (FVTool) confirms that.
hfvt = fvtool(Hi, 'Analysis', 'info'); hfvt.Color = [1 1 1];
Notice that even though the interpolation filter is symmetric and thus has linear phase, the polyphase components are not necessarily symmetric and thus will not necessarily have exact linear phase. However, for each nonsymmetric polyphase filter, there is a mirror image polyphase filter which will have the exact same magnitude response with a mirror image group-delay that will compensate any phase distortion.
%set(hfvt, 'PolyphaseView','on', 'Analysis', 'grpdelay','Legend','on') hfvt.PolyphaseView = 'on'; hfvt.Analysis = 'grpdelay'; hfvt.Legend = 'on';
The input signal x[n] is a 7 kHz sinusoid sampled at 44.1 kHz.
N = 30; Fs = 44.1e3; n = (0:N-1).'; x = sin(2*pi*n*7e3/Fs); % Filter with a Direct-Form FIR Polyphase Interpolator. y1 = step(Hi,x);
The group-delay of the filter, in terms of input samples is half of the filter length minus one divided by the interpolation factor
delay = (length(Hi.Numerator)-1)/(2*L); t = delay*L+(0:L:L*length(x)-L); t1 = 0:length(y1)-1;
Display the output of the Direct-Form FIR Polyphase Interpolator and overlay the original signal (reference).
stem(t,x,'filled','k'); hold on stem(t1,y1); axis([0 90 -Inf Inf]) legend('Original signal','Interpolated Signal',2) xlabel('Samples') ylabel('Amplitude') fig = gcf; fig.Color = [1 1 1];
We compute the power spectral densities of both input and interpolated signal.
% Create an audio file reader and point to an audio file with sound sampled % at 48 kHz Ha = dsp.AudioFileReader('audio48kHz.wav'); % Create a spectrum analyzer to view the spectrum of the input and % interpolated audio. Hs = dsp.SpectrumAnalyzer('SampleRate',96e3,'ShowLegend',true,... 'SpectralAverages',10); % Design an interpolate-by-2 filter to interpolate the signal from 48 kHz % to 96 kHz L = 2; Hf = fdesign.interpolator(L,'Halfband'); Hi = design(Hf,'SystemObject',true);
The input is upsampled independently to 96 kHz by inserting a zero between every sample in order to plot the input and output spectrum simultaneously. To maintain the same power level, the upsampled signal is multiplied by the upsampling factor.
while ~isDone(Ha) x = step(Ha); % Original 48 kHz audio xu = L*upsample(x,L); % Insert a zero every other sample to compare y = step(Hi,x); % Interpolated 96 kHz audio (input is x, not xu) step(Hs,[xu,y]); end % Release Audio File Reader release(Ha);
As expected, the interpolation filter removes spectral replicas from the original signal.