THE AMBIGUITY DIAGRAM  

 

WAVEFORM2.M

 

ambiguity     waveform1     waveform3

 

function [reference, convolution] = waveform2(pts, slope)

  % Waveform #2 is a chirp signal

 

reference = cos(2 * pi * (- (slope * pts) + slope * ([1:pts]')) .* ([1:pts]') / pts); 

  % frequency increases over time

   

matchedir = reference;

for i = 1:pts

    matchedir(i) = reference(1 + pts - i);

end

  % Matchedir is the time-reversed version of reference 

 

frange = -5:0.01:5;

convolution = [];

for i = 1:length(frange)

   freq = frange(i) - (slope * pts);

   realsig = real(exp(j * 2 * pi * (freq + slope * ([1:pts]')) .* ([1:pts]') / pts));

   imagsig = imag(exp(j * 2 * pi * (freq + slope * ([1:pts]')) .* ([1:pts]') / pts));

     % Break signal into real and imaginary components

  

   realconv = conv(realsig, matchedir);

   imagconv = conv(imagsig, matchedir);

     % Convolve each part individually

  

   convolution = [convolution, sqrt((realconv .* realconv) + (imagconv .* imagconv))];

     % Build the convolution vector

end

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MOTIVATION – Why this is important

OBJECTIVE – What we hoped to achieve

AMBIGUITY DIAGRAM - What it is

AMBIGUITY DIAGRAM - How to read it

WAVEFORMS – The signals we analyzed

RESULTS – Results for CW and PCM

CHIRP - A closer look

POSSIBLE EXTENTIONS – What’s next

CODE - Fascinating stuff

ACKNOWLEDGMENTS - Who we have to thank