removed tr

track_audio.m

-clear;
-close all;
-clc;
-
-fs = 24414;
-chunks = 2048;
-dt = chunks/fs;
-
-[Bf, Af] = butter(3,8000/fs); % filter vectors
-
-
-%% Setup objects
-% Initialize localization models using braodband and subband settings
-dObj   = dataObject([],fs,10,2);
-
-% Settings for subband approach
-par_sub = genParStruct('cc_bBroadband',0,'cc_wSizeSec',winSec,...
-    'cc_hSizeSec',winSec/2,'cc_maxDelaySec',1.25e-3,...
-    'fb_lowFreqHz',fLowHz,'fb_highFreqHz',fHighHz,...
-    'fb_nERBs',1,'ihc_method','none',...
-    'loc_NSources',nSpeakers(hh));
-
-% Initialize localization models using braodband and subband settings
-mObj  = manager(dObj,'localization',par_sub);
-
-%% Model parameters
-sigma_w = 1;
-
-Q = [2/4*dt^4, 1/2*dt^3; 1/2*dt^3, dt^2]*sigma_w;   % Process noise covariance
-R = 1;                                              % Measurement noise covariance
-x = [0; 0];                                         % Initial state
-P = [10, 0; 0, 10];                                 % Initial state covariance
-
-A = [1, dt; 0, 1];                                  % System matrix
-c = [1; 0];                                         % Output vector
-
-% Check definiteness of covariance matrices
-if ~all(eig(Q) > 0) || ~all(eig(R) > 0) || ~all(eig(A) > 0)
-    error('All covariance matrices have to be positive definite.');
-end
-
-%% Initialization
-
-
-% Add necessary paths
-addpath('./tools');
-addpath('./ekfukf-toolbox');
-
-
-
-figure(1)
-
-N = 1; % The number of steps to run this stuff.
-
-% Initialize posterior mean and covariance
-posteriorMean = zeros(size(A, 1), N);
-posteriorCovariance = zeros(size(A, 1), size(A, 1), N);
-
-
-% =======================================================
-% Main loop - Perform localization and tracking
-% =======================================================
-tic();
-t_old = toc();
-for l = 1:N
-    audio = get_audio();
-    t_new = toc();
-    dti = t_new - t_old();
-    % Request processing
-    mObj.processSignal(audio);
-    azimEst = dObj.localization{1}.Data(end,1); % There might be an issue with several sources here!
-    % Perform Kalman filter prediction and update, TODO: consider changing this
-    % crappy filter for a PF
-    
-    
-    Qi = [1/4*dti^4+1e-6, 1/2*dti^3; 1/2*dti^3, dti^2]*sigma_w;   % Process noise covariance
-    Ai = [1, dti; 0, 1];
-    [x, P] = kf_predict(x, P, Ai, Qi);
-    [x, P] = kf_update(x, P, azimEst, c', R);
-    
-    posteriorMean(:, l) = x;
-    posteriorCovariance(:, :, l) = P;
-    %pause(max0))
-    t_old = t_new;
-end
-
-% Plot measurements
-subplot(2, nFiles / 2, k);
-timeAxis = linspace(0, nSamples / fsHz, nFrames);
-plot(timeAxis, measuredLocations, 'x', 'LineWidth', 2);
-axis([0, nSamples / fsHz, -90, 90]);
-xlabel('Time / s');
-ylabel('Azimuth / deg');
-grid on; hold on;
-plot(timeAxis, posteriorMean(1, :), 'g', 'LineWidth', 2);
-
-% Plot ground truth
-plot(timeAxis, gtTrajectory, 'r--', 'LineWidth', 2);
-legend('Measurements', 'Estimated trajectory', 'Ground truth');
-
-% Compute RMSE
-rmse = sqrt(sum((posteriorMean(1, :) - gtTrajectory).^2) ./ nFrames);
-
-if ~strcmpi(noiseType, 'none')
-    title([upper(soundType), ', ', upper(noiseType), ' NOISE AT ', ...
-        num2str(snr), ' dB SNR, ', 'RMSE: ', num2str(rmse), '°']);
-else
-    title([upper(soundType), ', NO NOISE, ', 'RMSE: ', ...
-        num2str(rmse), '°']);
-end