%% Inout Data for DoA Estimation with ANN 
% Cognitave, Inc.
% Programmer: Mahdi Haghzadeh, CEO
% Revisions: 
%           Date: 1/15/2018 
%% Modeling the Received Array Signals
% Define a uniform linear array (ULA) composed of 10 isotropic antennas. The 
% array element spacing is 0.5 meters.

N = 10;
ula = phased.ULA('NumElements',N,'ElementSpacing',0.5);

%% 
% Simulate the array output for one incident signal. The signal is incident 
% from 90∞ in azimuth. It's elevation angles is randomly generated. We assume 
% that the directione are unknown and need to be estimated. Simulate the 
% baseband received signal at the array demodulated from an operating frequency of 300 MHz.

fc = 76.5e9;                               % Operating frequency
fs = 8192;                                % Sampling frequency
lambda = physconst('LightSpeed')/fc;      % Wavelength
pos = getElementPosition(ula)/lambda;     % Element position in wavelengths
%rs = rng(2012);                           % Set random number generator
randAng = randi(90)
ang1 = [randAng, 0];                           % Direction of the signals
angs = ang1;
Nsamp = 1024;                             % Number of snapshots
noisePwr = 0.01;                          % Noise power
signal = sensorsig(pos,Nsamp,angs,noisePwr);
%% 
% Because a ULA is symmetric around its axis, a DOA algorithm cannot uniquely 
% determine azimuth and elevation. Therefore, the results returned by these high-resolution 
% DOA estimators are in the form of broadside angles. An illustration of broadside 
% angles can be found in the following figure.
% 
% 
% 
% Calculate the broadside angles corresponding to the two incident angles.