Code covered by the BSD License

# Introduction to Object-Oriented Programming in MATLAB(R) Webinar

### Jiro Doke (view profile)

09 Apr 2009 (Updated )

Files from the "Introduction to Object-Oriented Programming in MATLAB(R)" Webinar.

sensor
```classdef sensor
%SENSOR Class for Sensor Staring Array
%   This is the prototype class for the sensor Staring Array.
%   It is a bare bones class that needs refinement.

% Copyright 2008 The MathWorks, Inc.

properties
numDetector = 96
numSamples  = 1
sampleRate  = 1/.3e-7
noiseRatio  = 50
wavelength  = 3e8/12e7
spacing     = 1.25
sensitivity = 0.8
end

methods
function arrivalAngles = computeAoA(aSensor, target)
arrayData          = sensorSignal(aSensor, target) ;
arrivalAngles      = determineAoA(aSensor, arrayData);
end
end
end

%% Helper Sub Functions for Class Methods
function targetAoA = determineAoA(sensor,arrayData)
% COMPUTEAOA  Estimate the direction of arrival of the sources in the
% sensor array data set using simplistic peak finding method
% Example:
%  angels=doa(ds)

nearestPower2  = 2^ceil(log2(sensor.numDetector))         ;

%% Compute the FFT of the sensor data

%% Compute the amplitudes
detectRange    = sensor.sensitivity*max(mags)             ;%dynamic detect range
targetIndex    = peakdet(mags,detectRange)                ;%find the peaks

if ~isempty(targetIndex)
targetAoA   = sort(angles(targetIndex(:,1))*180)       ;%angles
else
targetAoA   = []                                       ;%angles
end

%% Plot the results
title ([num2str(length(targetAoA)) ' Identified Targets']);
xlabel('Degrees')                                     ;
ylabel('Amplitude'  )                                     ;

%% Plot vertical lines on the targets
for n = 1:length(targetAoA)
vline(targetAoA, 'r')                                  ;
end

end % function computeAoA

function [maxtab, mintab]=peakdet(v, delta)
%PEAKDET Detect peaks in a vector
%        [MAXTAB, MINTAB] = PEAKDET(V, DELTA) finds the local
%        maxima and minima ("peaks") in the vector V.
%        A point is considered a maximum peak if it has the maximal
%        value, and was preceded (to the left) by a value lower by
%        DELTA. MAXTAB and MINTAB consists of two columns. Column 1
%        contains indices in V, and column 2 the found values.
% Eli Billauer, 3.4.05 (Explicitly not copyrighted).
% http://www.billauer.co.il/peakdet.html
% This function is released to the public domain; Any use is allowed.

maxtab = [];
mintab = [];

v = v(:); % Just in case this wasn't a proper vector

if (length(delta(:)))>1
error('Input argument DELTA must be a scalar');
end

if delta <= 0
error('Input argument DELTA must be positive');
end

mn = Inf; mx = -Inf;
mnpos = NaN; mxpos = NaN;

lookformax = 1;

for i=1:length(v)
this = v(i);
if this > mx, mx = this; mxpos = i; end
if this < mn, mn = this; mnpos = i; end

if lookformax
if this < mx-delta
maxtab = [maxtab ; mxpos mx]; %#ok
mn = this; mnpos = i;
lookformax = 0;
end
else
if this > mn+delta
mintab = [mintab ; mnpos mn]; %#ok
mx = this; mxpos = i;
lookformax = 1;
end
end
end

end % function peakdet

% MAGFFT Calculate the magnitude square of the FFT of the
% Example:
%  result=magfft(s,128);

%% Preallocate store of magnitudes and frequencies

%% Take the sum over each sensor array sample
for k=1:sensor.numSamples
avbig(1:sensor.numDetector) = arrayData(1,:)            ;
mag(k,:)                    = abs(fftshift(response)).^2;%Mag squared
end

%% Combine the results if available
if sensor.numSamples > 1
mags = sum(mag);
else
mags = mag;
end

end % funciton magfft

function arrayData = sensorSignal(sensor, target)

% Initialize output vector
arrayData  = zeros(sensor.numSamples,sensor.numDetector);

% Identify total number of targets
numTargets = length(target)                             ;

% Detector Positions (m)
orgX       = (sensor.numDetector+1)/2;
detectPos  = ((1:sensor.numDetector) - orgX)*sensor.spacing;%Sensors row vector

% For each source/target, calculate the amplitue at the array and sum
for n=1:numTargets
bearing   = 0.5*pi-target(n).AoA*pi/180             ;%Source angle
tx        = target(n).range*cos(bearing)            ;%Source X position
ty        = target(n).range*sin(bearing)            ;%Source Y position
distance  = sqrt((tx+detectPos).^2+(ty)^2)          ;%Distance to source
timeDelay = distance/target(n).signal.spdOfLight    ;%Time delay to source
for k=1:sensor.numSamples
arrayData(k,:) = arrayData(k,:) + ...
target(n).signal.amp*exp(j*(timeDelay-k/sensor.sampleRate)* ...
2*pi*target(n).signal.freq);
end
end

for k=1:sensor.numSamples
arrayData(k,:)=noisyvar(arrayData(k,:).',sensor.noiseRatio,numTargets).';
end

end

function y=noisyvar(x,snr,num)
% Add noise to given signal
A     = 1;
noise = (A/(sqrt(2)))*randn(length(x),1)+(A/(sqrt(2)))*j*randn(length(x),1);
powx  = (x'*x)/length(x)/num;
pown  = (noise'*noise)/length(x);
rwant = 10^(snr/10);
nwant = (noise/sqrt(pown))*sqrt(powx/rwant);
y     = x+nwant;
end
```