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AWR1642BOOST: Capture_demo Matlab file compatibility

Part Number: AWR1642BOOST

Good day

When you use the Matlab file - capture_demo.m to post process the saved .dat file saved from the mmWave demo visualizer, you get an error "Dimensions of matrices being concatenated are not consistent" - even if you replace the number of chirps, etc etc etc etc with the ones matching your profile.

the specific lines throwing the error:

fid = fopen('my_data.dat', 'r');
rawData = textscan(fid, '%s', 'Delimiter', '', 'headerLines',1);
data = cell2mat(cat(2, rawData{:}));

My question is this, is the capture_demo.m (created for ver 1) , compatible with decoding the dat file obtained from newer versions e.g. the mmWave_Demo_Visualizer ver 3.1.0?

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%
%  capture_demo.m
%
%  Description:
%  This file is a sample MATLAB script to process the data captured from
%  Capture Demo.
%  It reads data from file("ccs_data.dat") which is saved from CCS or 
%  file("lvds_data.csv") which is saved from LVDS + TSW setup. 
%  It then generates first FFT graph of the captured data.
%  Please refer to the capture demo script for the parameters used in the
%  demo. Such as number of samples, number of chirps etc.
%  
%  Usages:
%  To call this function please enter:
%  "capture_demo(1)" to process CCS memory data file ccs_data.dat
%  or
%  "capture_demo(2)" to process LVDS data file lvds_data.csv

function capture_demo(fileSelect)
%clear all;
close all;

% Global variables
% Please align with the actual demo for these variables.

% Number of samples
K = 256;
% Number of chirps
Nchirp = 128;
% Slope const (MHz/usec)
freqSlope = 40 * 1e12;
% Velosity of light
C = 3e8;
% ADC sampling rate
sampleRate = 8000 * 1e3;
% ADC start time (usec)
adcStartTime = 5 * 1e-6;
% Start frequency (GHz)
startFreq = 77 * 1e9;
% ramp End time
rampEndTime = 40 * 1e-6;

if fileSelect == 1
    %Read in CCS memory file and convert to real number
    fid = fopen('ccs_data.dat', 'r');
    rawData = textscan(fid, '%s', 'Delimiter', '', 'headerLines',1);
    data = cell2mat(cat(2, rawData{:}));
    % Convert data to decimal, and reshape in two columns for I and Q
    dataDec = hex2dec(data);
    dataDec = dataDec - ( dataDec >=2.^15).* 2.^16;
    rad_in = reshape(dataDec, [2, length(dataDec)/2]).';
    fclose(fid);
elseif fileSelect == 2
    %Read in LVDS csv file
    data = csvread('lvds_data.csv');
    %reshape in two columns for I and Q
    [row col] = size(data);
    rad_in = reshape(data.', [2, row*col/2]).';
else
    fprintf('Please enter:\n');
    fprintf('"capture_demo(1)" to process CCS memory data file ccs_data.dat\n');
    fprintf('or\n');
    fprintf('"capture_demo(2)" to process LVDS data file lvds_data.csv\n'); 
    return;
end

% Plot I and Q
figure(1);
plot(rad_in(:,1));grid on;
hold on;
plot(rad_in(:,2),':r');grid on;
xlabel('ADC sample index');
ylabel('Sample value');
title('ADC raw data');

% Change to complex data and Calculate average
% To handle static object only, use average as an example filter.
frame = rad_in(1:K*Nchirp,1) + i*rad_in(1:K*Nchirp,2);
chAve = zeros(K,1);
avgChirp = Nchirp;
for nn = 1:avgChirp
    chAve = chAve + frame((nn-1)*K+1:(nn-1)*K+K);
end
chAve = chAve/avgChirp;

% Calculate range
rangeResolutionsInMeters = C * sampleRate / (2 * freqSlope * K);
rangeIdxToMeters = C * sampleRate / (2 * freqSlope * K);
rangeBin = linspace(0, K * rangeIdxToMeters, K);

% Do FFT on chirp average and plot results
fftResult = fft(chAve);

% Do FFT on chirp average and plot results
figure(2);
plot(rangeBin, abs(fftResult), '-m'); grid on;
hold on;
xlabel('range (m)');
title('Range FFT');



attached, capture_demo.m