MATLAB: Extract and store valuable data in vectors

radar signalstore pulses in vector

I have a signal (vector) consists of many blocks (for example five blocks）.I want to extract, separate, these blocks (that contain a valuable information ) from the main signal and store every block in a vector. This is real data and the 5 valuable information in the example are not always in same location.

For example like:

So if I have an input vector (V), The result , in our case, should be five mini vectors (v1, v2, v3, v4, v5).

I tried to apply this method: If a specific consecutive elements from (V) vector have a value above a threshold (for example 0.02 > Thr) start put the elements in a a mini vector, but it does not work because values in the input vector (V) are getting positive and negative.

Best Answer

Simple thresholding won't work because in each burst there are dips that you probably want to keep. Luckily for you I solved this same problem for another person in this discussion: http://www.mathworks.com/matlabcentral/answers/229678#answer_185935 :

% Setup - read in the signal and plot it.
s=load('signal.mat')
signal = s.coarse_d;
subplot(3,1,1);
plot(signal, '-', 'Color', [0,.5,0]);
grid on;
% MAIN CODE IS THE FOLLOWING TWO LINES OF CODE.
% Threshold the signal
lowSignal = abs(signal) < 0.1;
% Remove stretches less than 10,000 elements long.
% And invert it to get the high signal areas instead of the quiet areas.
lowSignal = ~bwareaopen(lowSignal, 10000);
% Now we're done.  Plot the results.
subplot(3,1,2);
plot(lowSignal, 'b-', 'LineWidth', 2);
grid on;
% Plot both on the same graph now.
subplot(3,1,3);
plot(signal, '-', 'Color', [0,.5,0]);
hold on;
plot(lowSignal, 'b-', 'LineWidth', 2);
grid on;

As you can see it identifies each "block" but leaves the inside of the block intact.

Related Solutions

MATLAB: Extract valuable data from signal

Try something like this, where I take the absolute value, then filter it to get rid of the oscillating parts, then take the difference, and finally extract the 5 bursts:

clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
clear;  % Erase all existing variables. Or clearvars if you want.
workspace;  % Make sure the workspace panel is showing.
format longg;
format compact;
fontSize = 20;
% Generate sample data.
signal = 0.003 * rand(1, 550) - 0.0015
signal(50:100) = 0.03 * rand(1, 51) - 0.015
signal(150:200) = 0.03 * rand(1, 51) - 0.015
signal(250:300) = 0.03 * rand(1, 51) - 0.015
signal(350:400) = 0.03 * rand(1, 51) - 0.015
signal(450:500) = 0.03 * rand(1, 51) - 0.015
subplot(3, 1, 1);
plot(signal);
title('Original Signal', 'FontSize', fontSize);
grid on;
% Enlarge figure to full screen.

set(gcf, 'units','normalized','outerposition',[0 0 1 1]);
% Take absolute value and median filter to get rid of oscillations.
filteredSignal = medfilt1(abs(signal), 13);
subplot(3, 1, 2);
plot(filteredSignal);
title('Filtered Signal', 'FontSize', fontSize);
% Find the quiet parts between the bursts.
quietParts = filteredSignal < 0.002;
subplot(3, 1, 3);
plot(quietParts, 'LineWidth', 3);
ylim([0 1.2]);
title('Quiet Parts', 'FontSize', fontSize);
% Find the starting and ending elements of the bursts.
startingBlockIndexes = find(diff(quietParts) < 0)
endingBlockIndexes = find(diff(quietParts) > 0)
% Extract the 5 blocks (known to be exactly 5)
v1 = signal(startingBlockIndexes(1):endingBlockIndexes(1));
v2 = signal(startingBlockIndexes(2):endingBlockIndexes(2));
v3 = signal(startingBlockIndexes(3):endingBlockIndexes(3));
v4 = signal(startingBlockIndexes(4):endingBlockIndexes(4));
v5 = signal(startingBlockIndexes(5):endingBlockIndexes(5));
% Plot the 5 signals.
figure;
subplot(5, 1, 1);
plot(v1);
grid on;
title('V1', 'FontSize', fontSize);
subplot(5, 1, 2);
plot(v2);
grid on;
title('V2', 'FontSize', fontSize);
subplot(5, 1, 3);
plot(v3);
grid on;
title('V3', 'FontSize', fontSize);
subplot(5, 1, 4);
plot(v4);
grid on;
title('V4', 'FontSize', fontSize);
subplot(5, 1, 5);
plot(v5);
grid on;
title('V5', 'FontSize', fontSize);
% Enlarge figure to full screen.
set(gcf, 'units','normalized','outerposition',[0 0 1 1]);

MATLAB: Decompose Data int a Matrix

The data you want is when the ‘lowSignal’ vector is equal to 1. If each column in your matrix has one pulse from that record, the separation has already been done. By definition, each column is a pulse, so if your matrix is ‘M’ and it is of size (Nx8), where ‘N’ is the number of rows, to get the first and eighth pulses:

Pulse_1 = M(:,1);
Pulse_8 = M(:,8);

Best Answer

Related Solutions

MATLAB: Extract valuable data from signal

MATLAB: Decompose Data int a Matrix

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