📄 nene.m
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function [s,V] = nene(z,rho,theta)% function NENE.M% Nearest neighbor approximation algorithm% [s,V] = nene(z,rho,theta)% z = M by N matrix with samples in frequency domain % rho, theta = radius and angles ofdata points% interpolated matrix% V = vector that includes [X0 dkx dky fl]close all% Variables bursts bursts = size(z,1); pul_burst = size(z,2); rho = rho.*(4*pi/3e8); %% frequency matrix in rad/mt rhov = rho(1,:); drho = rhov(2) - rhov(1); ac = theta(bursts,1) - theta(1,pul_burst);% Points of Interpolation x = linspace(min(rhov), max(rhov)*cos(ac/2),pul_burst); y = min(rhov)*tan(ac/2)*linspace(-1,1,bursts); [fxi,fyi] = meshgrid(x,y); fxd = rho.*cos(theta); fyd = rho.*sin(theta); dkx = fxi(1,2) - fxi(1,1); dky = fyi(2,1) - fyi(1,1); X0 = pi/(rhov(2) - rhov(1));% Interpolation flops(0) s = zeros(size(z)); for a = 1:bursts, for b = 1:pul_burst, rr = sqrt(fxi(a,b)^2 + fyi(a,b)^2); tt = atan2(fyi(a,b),fxi(a,b)); n = 1 + fix((rr - min(rhov))/drho); c = rr - (min(rhov) + drho*(n-1)); t2 = (theta(:,n+1) - theta(:,n))*c/drho + theta(:,n);
if a==128
tt=tt-0.001;
end k = min(find(tt<t2)) - 1; vx = [fxd(k,n) fxd(k+1,n) fxd(k+1,n+1) fxd(k,n+1)]; vy = [fyd(k,n) fyd(k+1,n) fyd(k+1,n+1) fyd(k,n+1)]; d = sqrt((fxi(a,b)-vx).^2)+sqrt((fyi(a,b)-vy).^2); kk=[k n;k+1 n;k+1 n+1;k n+1]; [c1,c2] = min(d); k1 = kk(c2,1); k2 = kk(c2,2); s(a,b) = z(k1,k2); end; end fl = flops; V = [X0 dkx dky fl];
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