ADBF.zip_ADBF_machinery2x3_波束形成 ADBF

% Radiation Pattern for N-Element Adaptive Array % with Multiple Narrow-Band Noise Jammers %----------------------------------------------- % adap_apple2.m clear;clc; %Adaptive Array Parameters (default values) nx= 3; % Number of Noise Jammers n=8; % Number of Array Elements thetas =0; %Target Angle - deg d=.1; % Noise Power / Jammer Power % Use a dialog box to get input header= 'Adaptive Array Parameters'; prompt = {'Number Noise Jammers', 'Number Array Elements',... 'Target Angle - deg', 'Noise / Jam Ratio'}; default = {num2str(nx), num2str(n), num2str(thetas),... num2str(d)}; response = inputdlg(prompt, header, 1, default); fields = {'nx', 'n', 'thetas','d'}; input = cell2struct(response,fields,1); % Convert cell structure created by dialog box back to numbers nx = str2num(input.nx); n = str2num(input.n); thetas = str2num(input.thetas); d = str2num(input.d); if nx>n-1; error('Array Exceeds Degree of Freedom'); end; beam_wid_rad=2*asin(2/n); beam_wid=180*beam_wid_rad/pi; for loop = 1:nx; if loop<=2; thetaj(loop)=30+15*(loop-1); else thetaj(loop)=-30-15*(loop-3); end; ax(loop)=1; header = ['Standoff Jammer #' num2str(loop)]; prompt = {'Jammer Angle (deg)', 'Relative Jam Power'}; default = {num2str(thetaj(loop)),num2str(ax(loop))}; response = inputdlg(prompt, header, 1, default); fields = {'thetaj','ax'}; input = cell2struct(response,fields,1); %Convert cell structure created by dialog box back to numbers thetaj(loop) = str2num(input.thetaj); if abs(thetaj(loop))<beam_wid/2+3; error('Jammer Angle in Main Array Beam') end; ax(loop) = str2num(input.ax); end; for i=1:nx; thetaj(i)= thetaj(i)*pi/180; % Jam Angle - rad psinj(i)=pi*sin(thetaj(i)); % Jam Angle - sin space end; % Array Angle theta= -90:.1:90; % Pattern Angle - deg thetar= pi*theta/180; % Pattern Angle - rad % Weight Calculation % Covariance Matrix using Applebaum's Transformation I=ones(n); Z=zeros(n); for i=1:nx; for k=1:n; Z(k,k)=exp(j*(k-1)*psinj(i)); end; Rx=ax(i)*conj(Z)*I*Z; if i==1;R=Rx; else R=Rx+R;end; % Jammer Covariance Matrix end; pj=sum(ax); % Total Jam Power R=R/pj+d*eye(n); % Sum of Jammer + Noise Covariance Matrix % Signal thetas=pi*thetas/180; % Signal Angle - rad psins=pi*sin(thetas); % Signal Angle Sin Space S=ones(n,1); %S=[1;1]; % Steering Vector w=d*inv(R)*S; % Weight Vector Ms=S*S'; % Signal Covariance Matrix Ps=w'*Ms*conj(w); % Signal Power fac=sqrt(Ps); % Normalize Factor for Ps=1 wn=w/fac % Normalized Weights % Array Output for i=1:1801; psi(i) = pi*sin(thetar(i)); % Array Angle in Sin Space for k=1:n; A(1,k)=exp(j*(k-1)*(psi(i)-psins)); end; v(i)=abs(sum(A*w/fac)); % Array Voltage Pattern end; p= v.^2; % Array Power Out Pattern figure(1); plot(theta,p);grid; xlabel('Degrees'); ylabel('Amplitude'); title(['Antenna Pattern ',num2str(n),'-Element Adaptive Array']); axis([-60,60,0,1]); hold on % Grid Lines x=-60 to 60, space=5;y=0-1;space=.05 xl=-60;xh=60;yl=0;yh=1;nx=25;ny=21; hx=gridline(xl,xh,nx,yl,yh,ny); hold off figure(2) p_db=10*log10(p); plot(theta,p_db);grid; xlabel('Degrees'); ylabel('Amplitude - dB'); title(['Antenna Pattern ',num2str(n),'-Element Adaptive Array']); axis([-60,60,-50,0]);