肯塔基大学分布式音频阵列工具箱matlab源码

filenames(:,1) = { ... 'imp400_5600___c_-1_-1.mat';... 'imp400_5600___c_-1_0.mat';... 'imp400_5600___c_-1_1.mat';... 'imp400_5600___c_0_-1.mat';... 'imp400_5600___c_0_0.mat';... 'imp400_5600___c_0_1.mat';... 'imp400_5600___c_1_-1.mat';... 'imp400_5600___c_1_0.mat';... 'imp400_5600___c_1_1.mat'}; %... filenames(:,2) = { ... 'imp400_5600_n_c_-1_-1.mat';... 'imp400_5600_n_c_-1_0.mat';... 'imp400_5600_n_c_-1_1.mat';... 'imp400_5600_n_c_0_-1.mat';... 'imp400_5600_n_c_0_0.mat';... 'imp400_5600_n_c_0_1.mat';... 'imp400_5600_n_c_1_-1.mat';... 'imp400_5600_n_c_1_0.mat';... 'imp400_5600_n_c_1_1.mat'}; % ... filenames(:,3) = { ... 'imp400_600___c_-1_-1.mat';... 'imp400_600___c_-1_0.mat';... 'imp400_600___c_-1_1.mat';... 'imp400_600___c_0_-1.mat';... 'imp400_600___c_0_0.mat';... 'imp400_600___c_0_1.mat';... 'imp400_600___c_1_-1.mat';... 'imp400_600___c_1_0.mat';... 'imp400_600___c_1_1.mat'}; %... filenames(:,4) = { ... 'imp400_600_n_c_-1_-1.mat';... 'imp400_600_n_c_-1_0.mat';... 'imp400_600_n_c_-1_1.mat';... 'imp400_600_n_c_0_-1.mat';... 'imp400_600_n_c_0_0.mat';... 'imp400_600_n_c_0_1.mat';... 'imp400_600_n_c_1_-1.mat';... 'imp400_600_n_c_1_0.mat';... 'imp400_600_n_c_1_1.mat'}; %... filenames(:,5) = { ... 'nos___c_-1_-1.mat';... 'nos___c_-1_0.mat';... 'nos___c_-1_1.mat';... 'nos___c_0_-1.mat';... 'nos___c_0_0.mat';... 'nos___c_0_1.mat';... 'nos___c_1_-1.mat';... 'nos___c_1_0.mat';... 'nos___c_1_1.mat'}; %... filenames(:,6) = { ... 'nos_n_c_-1_-1.mat';... 'nos_n_c_-1_0.mat';... 'nos_n_c_-1_1.mat';... 'nos_n_c_0_-1.mat';... 'nos_n_c_0_0.mat';... 'nos_n_c_0_1.mat';... 'nos_n_c_1_-1.mat';... 'nos_n_c_1_0.mat';... 'nos_n_c_1_1.mat'}; %... filenames(:,7) = { ... 'words___c_-1_-1.mat';... 'words___c_-1_0.mat';... 'words___c_-1_1.mat';... 'words___c_0_-1.mat';... 'words___c_0_0.mat';... 'words___c_0_1.mat';... 'words___c_1_-1.mat';... 'words___c_1_0.mat';... 'words___c_1_1.mat'}; %... filenames(:,8) = { ... 'words_n_c_-1_-1.mat';... 'words_n_c_-1_0.mat';... 'words_n_c_-1_1.mat';... 'words_n_c_0_-1.mat';... 'words_n_c_0_0.mat';... 'words_n_c_0_1.mat';... 'words_n_c_1_-1.mat';... 'words_n_c_1_0.mat';... 'words_n_c_1_1.mat'}; fout = {'hopewb.mat'; ... 'hopewbnos.mat'; ... 'hopenb.mat'; ... 'hopenbnos.mat'; ... 'hopewnb.mat'; ... 'hopewnbnos.mat'; ... 'hopewrd.mat'; ... 'hopewrdnos.mat'}; envparametersexp5_15_2006 pflag =0; pars.snrtype = 'p'; batar = [0 .1 .2 .3 .4 .5 .6 .7 .8 .9 1]; % Beta values to be tested trez = 30e-3; % Processing Window Length In seconds % Room Resolution: Step through cartesion grid for mic and sound source % plane rez = .02; % In meters froom = [-3.25 -3.75 0; 3.25 3.75 3]'; % Opposite Corner Points of room % All vertcies in image plane v = [froom(1:2,1), [froom(1,1); froom(2,2)], froom(1:2,2), [froom(1,2); froom(2,1)]]; v = [v; ones(1,4)*mean(fov(3,:))]; gridax = {[fov(1,1):rez:fov(1,2)], [fov(2,1):rez:fov(2,2)], [fov(3,1):rez:fov(3,2)]}; cfreq = [300, 7000]; % Critical frequency range where most signal energy resides mposperim = mpos; % Find max distance (delay) over all mic pair, this represents % and upper bound on all requried relative delays when scanning over % the FOV [rm, nm] = size(mposperim); prs = mposanaly(mposperim,2); maxmicd = max(prs(:,3)); % Extra delay time in seconds for padding window of data textra = maxmicd(1)/c; [posnum, typenum] = size(filenames); snrs = [1 4 6]; % Selecte particualr SNR values from recorded data for ktype = 1:typenum for k = 1:posnum filenames{k,ktype} load(['FoamOnly/' filenames{k,ktype}]); flim = 2*cfreq/fs; % Set frequency limit on PHAT transform % Initalize performance metric arrays for new file type if k == 1 tmpr = cell(length(snrs), length(batar)); % Initalize target magnitude array lerpr =cell(length(snrs), length(batar)); % Initalize position error array nmpr = cell(length(snrs), length(batar)); % Initalize noise magnitude array for target plus noise frames stpn = cell(length(snrs), length(batar)); % Initalize mean peak target per channel to rms noise in target frame ratio nompr = cell(length(snrs), length(batar)); % Initalize noise magnitude array for noise only frames stpno = cell(length(snrs), length(batar)); % Initalize mean peak target per channel to rms noise in noise only frame ratio end % Adjust target locations if tloc(1) == -1 & tloc(2) == -1 tloc(1) = tloc(1); tloc(2) = tloc(2) + .15; elseif tloc(1) == 0 & tloc(2) == -1; tloc(1) = tloc(1) - .015; tloc(2) = tloc(2) - .02+.15; elseif tloc(1) == 1 & tloc(2) == -1 tloc(1) = tloc(1) + 0.015; tloc(2) = tloc(2) + .15; elseif tloc(1) == -1 & tloc(2) == 0 tloc(1) = tloc(1) -.01; tloc(2) = tloc(2) + .15 + .01; elseif tloc(1) == -1 & tloc(2) == 1 tloc(1) = tloc(1); tloc(2) = tloc(2) + .15 - .01; elseif tloc(1) == 0 & tloc(2) == 0 tloc(1) = tloc(1) -.01; tloc(2) = tloc(2) +.15 -.005; elseif tloc(1) == 0 & tloc(2) == 1 tloc(1) = tloc(1)-.015; tloc(2) = tloc(2) + .15 - .01; elseif tloc(1) == 1 & tloc(2) == 0 tloc(1) = tloc(1)+.02; tloc(2) = tloc(2)+.15-.04; elseif tloc(1) == 1 & tloc(2) == 1 tloc(1) = tloc(1)+.015; tloc(2) = tloc(2)+.15-.015; end % Create corresponding time axis tax = [0:length(y)-1]/fs; winlen = ceil(fs*trez); % WIndow lenght in samples wininc = round(fs*trez/2); % WIndow increment in samples prez = ceil(fs*rez*sqrt(2)/c); % Time duration corresponding to 1 REZ pixel prez = [300]*prez; % Time interval for power integration (up to TREZ limit) [rsam, cmics] = size(y); % Get size in samples and mic channels of total mic recordings seglen = ceil(fs*(textra)) +winlen; % Get total segment lenght to account of max delay differences of potential sounds tapwin = flattap(seglen,20); % Create a flat window to taper edges winrec = tapwin*ones(1,cmics); % Extend window to cover array channels [b,a] = butter(4,cfreq(1)/(2*fs), 'High'); % Filter out room noise y = filtfilt(b,a,y); % SNR value loop for kpn=1:length(snrs) kp = snrs(kpn) % Assign index to SNR location % Get indecies for segment corresponding to SNR signal itax = find(tax >= par.targetb(kp) & tax <= par.targete(kp)); hs = y(itax,:); % Extract segement to identify peaks and window to ensure target is included in processing window env = abs(hs); [mv, cmax] = max(max(env)); % Find channel with stronget signal [mx, rmax] = max(env(:,cmax(1))); % Find sample with strongest peak center window there sed = rmax(1) - 1 + itax(1) + round(winlen/2); % Initial signal window index sst = sed - seglen; if kp > length(par.noiseb) itax = find(tax >= par.noiseb(end) & tax <= par.noisee(end)); else itax = find(tax >= par.noiseb(kp) & tax <= par.noisee(kp)); end nst = itax(1); % Initial signal window index ned = nst + seglen; snr = snrarray(y([sst:sed],:),y([nst:ned],:),pars); snrexp(k,kpn) = 10*log10(snr); for batak = 1:length(batar) bata = batar(batak); % Create Images from RF Perimeter Arr