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classdef sads
% Sensor Array Data Set Class
properties
Data % Sampled sensor data
SampleRate % Sample rate (Hz)
Spacing % Spacing of array (m)
Name % Sensor array test run name
end
properties (Access=private)
Wavelength % Wavelength of sources (m)
end
properties (Constant)
c=3e8; % Speed of wave in medium (m/s)
end
properties (Dependent)
NumSensors % Number of sensors
NumSamples % Number of samples
end
methods
function obj=sads(Data, Wavelength,SampleRate,Spacing,Name)
% SADS Create sensor array data set
% Example:
% sads(Data, Wavelength,SampleRate,Spacing,Name)
obj.Data=Data;
obj.SampleRate=SampleRate;
obj.Spacing = Spacing;
obj.Name=Name;
obj.Wavelength=Wavelength;
end
function [mags, fflip]=magfft(obj,zeroPadTo)
% MAGFFT Calculate the magnitude square of the FFT of the
% sensor array sample data, zeropadding by zeroPadTo elements
% Example:
% result=magfft(s,128);
mag=zeros(obj.NumSamples,zeroPadTo); % Preallocate store of magnitudes
f=asin((-0.5:1/(zeroPadTo-1):0.5)*obj.Wavelength/obj.Spacing)/pi; % Frequencies
fflip=fliplr(f); % Flip frequencies
% Take the sum over each sensor array sample
for k=1:obj.NumSamples
avbig=zeros(1,zeroPadTo); % Zero pad
avbig(1:obj.NumSensors)=obj.Data(1,:);
response=fft(avbig)/zeroPadTo; % FFT of normalized signal
mag(k,:)=abs(fftshift(response)).^2; % Mag squared of FFT
end
mags=sum(mag);
end
function NumSensors=get.NumSensors(obj)
% Get NumSensors property
NumSensors=size(obj.Data,2);
end
function NumSamples=get.NumSamples(obj)
% Get NumSamples property
NumSamples=size(obj.Data,1);
end
function plot(obj)
% PLOT Plot the sensor array sample data set
% Example:
% plot(ds);
surf(real(obj.Data)',...
'EdgeLighting','flat','FaceLighting','none',...
'FaceColor',[1 1 1],...
'EdgeColor',[0 0 1]);
view([-55.5 74]);
title(obj.Name);
xlabel('Samples')
ylabel('Sensors')
zlabel('Amplitude')
xlim([1 obj.NumSamples]);
ylim([1 obj.NumSensors]);
set(gca,'xtick',(1:obj.NumSamples/8:obj.NumSamples));
end
function magfftplot(obj, zeroPadTo)
% MAGFFTPLOT Plot the magnitude square of the FFT of the sensor
% array data
% Example:
% magfftplot(s,128);
[mags, fflip]=magfft(obj, zeroPadTo);
semilogy(180*fflip,mags(1:zeroPadTo),'r');
grid
title(['Averaged Magnitude Squared FFT of: ' obj.Name]);
xlabel('Degrees');
ylabel('Amplitude');
end
function angles=doa(obj)
% DOA Estimate the direction of arrival of the sources in the
% sensor array data set using simplistic peak finding method
% Example:
% angels=doa(ds)
zeroPadTo=256;
[mags, fflip]=magfft(obj,zeroPadTo);
maxtab=peakdet(mags,.1); % Use peakdet function
angles=sort(fflip(maxtab(:,1))*180); % Angles
end
function obj=steer(obj,theta)
% STEER Steer array electronically by angle theta (in degrees),
% returning a new sensor array data set
% Example:
% s=steer(s,10);
delta=obj.Spacing; thetaR=theta*(pi/180);
Wc=2*pi*(obj.c/obj.Wavelength); % Source frequency in radians per sec
phaseShift=exp(-j*Wc*delta*(0:obj.NumSensors-1)*sin(thetaR)/obj.c);
obj.Data=bsxfun(@times,obj.Data,phaseShift); % Multiply by phaseshift
end
end
methods (Static)
function showarray(Targets,NumSensors,Spacing)
% SHOWARRAY Illustrate a sensor array with ideal sources
% Example:
% showarray(Targets,NumSensors,Spacing)
numTargets=size(Targets,1);
orgX=(NumSensors+1)/2; % Center of array on x-axis
% Plot sensors
plot((1:NumSensors)',zeros(NumSensors,1),'o');
axis tight
set(gca,'xtick',1:NumSensors); % Ensure tick marks at each sensor
set(gca,'ytick',[]); % Remove y tick marks
ylim([0 NumSensors/1.5]); % Set Y axis limit
hold on
% Plot normal to array (Array direction)
plot(ones(NumSensors,1).*orgX,(0:NumSensors-1)','--k');
% Plot Incident rays
for tar=1:numTargets
bearing=.5*pi-Targets(tar,1);
length_line=orgX;
rayX=length_line*cos(bearing)+orgX;
rayY=length_line*sin(bearing);
plot([rayX orgX]', [rayY 0]','r');
end
hold off
% Annotations
legend('Sensors','Direction of Array','Direction of Sources');
xlabel(['Sensor spacing is ',num2str(Spacing), ' m']);
title([int2str(NumSensors),' sensor array with ' int2str(numTargets) ' sources']);
end
end
end
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];
mn = this; mnpos = i;
lookformax = 0;
end
else
if this > mn+delta
mintab = [mintab ; mnpos mn];
mx = this; mxpos = i;
lookformax = 1;
end
end
end
end