SAR成像学习（二） “Hello World”版本matlab代码

上一次最后给出了一个成像算法的示例，下面是它对应的代码，里面已经有了初步的注释。
当然这个是个简单情况，但已经大概说明了流程。代码具体的解释，我打算先放一放，毕竟it is a long story，我们需要从长计议。后续章节将结合代码逐渐讲解一下成像的步骤。在合适的时间，我会具体讲解这些代码的意义，以及他忽略的部分。
代码来源已经注明，在此表示感谢！
数据下载地址

clear all; close all; clc;

% Tutorial: Focusing of SAR raw data
% Programmed by Diana Weihing & Stefan Auer
% Remote Sensing Technology 
% Technische Universit鋞 M黱chen
% 2011

%--------------------------------------------------------------------------

% A.) Load raw data

% Dummy image ('Test_Image')
%raw = load('Test_Image'); % type: field
%max_power = 2.1807e+008;

% Real SAR data ('ERS')
raw = load('ERS'); % type: field
max_power = 10000;

% Multilooking on/off?
multilook = 1; % 0: no; 1: yes
ml_factor = 5; % multilooking factor (spatial)

% Get image size
fn = fieldnames(raw);
Raw_data = getfield(raw,fn{1});
size_azimuth = size(Raw_data,1);
size_range = size(Raw_data,2);
%--------------------------------------------------------------------------

% B.) Sensor parameters (ERS satellite)
fs=18.962468*10^6;          % Range Sampling Frequency [Hz]      
K_r=4.18989015*10^(11);     % FM Rate Range Chirp [1/s^2] --> up-chirp  
tau_p=37.12*10^(-6);        % Chirp duration [s]
V=7098.0194;                % Effective satellite velocity [m/s]
lambda=0.05656;             % Length of carrier wave [m]
R_0=852358.15;              % Range to center of antenna footprint [m]
ta=0.6;                     % Aperture time [s]  
prf=1679.902;               % Pulse Repitition Frequency [Hz]

%-------------------------------------------------------------------------- 

% C.) Display raw data
figure;
imagesc(abs(Raw_data));colormap('gray');
title('Raw data (unfocused)'); xlabel('Range pixels'); ylabel('Azimuth pixels');
axis equal; axis off;

%--------------------------------------------------------------------------

% D.) Define correlation chirp in range

% Basic definitions
range_chirp=zeros(1,size_range); % empty vector to be filled with chirp values
tau=-tau_p/2:1/fs:tau_p/2; % time axis in range
omega = -fs/2:1/tau_p:fs/2; % frequency axis in range ?

% Define chirp in range    
ra_chirp_temp = exp(1i.*pi.*K_r.*tau.^2); 

% Get size of chirp
size_chirp_r = length(tau);

%--------------------------------------------------------------------------

% Display range chirp (time + frequency domain)
figure;
subplot(2,1,1); plot(tau,real(ra_chirp_temp),'b'); hold on;
plot(tau,imag(ra_chirp_temp),'r');
title('Range chirp'); xlabel('Time axis [sec]'); ylabel('Amplitude');
xlim([min(tau) max(tau)]);
subplot(2,1,2); plot(omega, abs(fftshift(fft(ra_chirp_temp))));
title('Spectrum of range chirp'); xlabel('Frequency [Hz]'); ylabel('Absolute');
xlim([min(omega) max(omega)]);

%--------------------------------------------------------------------------

% Position chirp in range vector (centered)
% --> used for correlation procedure
range_chirp(ceil((size_range-size_chirp_r)/2):size_chirp_r+ceil((size_range-size_chirp_r)/2)-1)=ra_chirp_temp;

% Transform vector in frequency domain (fourier transform)
RANGE_CHIRP=fft(range_chirp);

% Define chirp for correlation 
% --> conjugate complex of signal chirp
CON_RANGE_CHIRP=conj(RANGE_CHIRP);

%--------------------------------------------------------------------------

% E.) Define correlation chirp in azimuth

% Basic definitions
azimuth_chirp=zeros(1,size_azimuth); % empty vector to be filled with chirp values
t=-ta/2:1/prf:ta/2; % time axis in azimuth
v=-prf/2:1/ta:prf/2; % frequency axis in azimuth??

% FM Rate Azimuth Chirp
K_a=-2*V^2/(lambda*R_0);

% Define chirp in azimuth
az_chirp_temp=exp(1i.*pi.*K_a.*t.^2); 

% Get size of chirp
size_chirp_a = length(t);

%--------------------------------------------------------------------------

% Display azimuth chirp (time + frequency domain)
figure;
subplot(2,1,1); plot(t,real(az_chirp_temp),'b'); hold on;
plot(t,imag(az_chirp_temp),'r');
title('Azimuth chirp'); xlabel('Time axis [sec]'); ylabel('Amplitude');
xlim([min(t) max(t)]);
subplot(2,1,2); plot(v, abs(fftshift(fft(az_chirp_temp))));
title('Spectrum of azimuth chirp'); xlabel('Frequency [Hz]'); ylabel('Absolute');
xlim([min(v) max(v)]);

%--------------------------------------------------------------------------

% Position chirp in azimuth vector (centered)
% --> used for correlation procedure
azimuth_chirp(ceil((size_azimuth-size_chirp_a)/2):size_chirp_a+ceil((size_azimuth-size_chirp_a)/2)-1)=az_chirp_temp;

% Transform vector in frequency domain (fourier transform)
AZIMUTH_CHIRP=fft(azimuth_chirp);

% Define chirp for correlation 
% --> conjugate complex of signal chirp
CON_AZIMUTH_CHIRP=conj(AZIMUTH_CHIRP);

%--------------------------------------------------------------------------

% F.) Focusing (= 2D correlation)

% Dummy matrix to be filled with processed data
processed=zeros(size_azimuth,size_range);

%-------------------------------------------------

% F.1) Range compression 
% --> correction in azimuth time - range frequency domain
% --> result in azimuth-range domain

for k1 = 1:size_azimuth
    vek = Raw_data(k1,:); % Select row in range  
    VEK = fft(vek); % Fourier Transform
    CORR = VEK.*CON_RANGE_CHIRP; % Multiply spectra
    if_vek = fftshift(ifft(CORR)); % Inverse Fourier Transform
    processed(k1,:) = if_vek;
end

clear vek VEK CORR if_vek

%-------------------------------------------------

% F.2) Azimuth compression 
% conducted in azimuth frequency - range time domain 

for k2 = 1:size_range
    vek = processed(:,k2); % select row in azimuth
    VEK = fft(vek); % Fourier Transform    
    CORR = VEK.*CON_AZIMUTH_CHIRP.'; % Multiply spectra if_vek = fftshift(ifft(CORR)); % Inverse Fourier Transform processed(:,k2) = if_vek; end % F.1) Range compression % --> correction in azimuth time - range frequency domain % --> result in azimuth-range domain clear vek VEK CORR if_vek %-------------------------------------------------------------------------- % G.) Spatial Multilooking % ERS: resolution in range: approx. 25 m, resolution in azimuth: approx. 5 m % Aim: pixel should have the same size in azimuth and range % solution: average 5 azimuth pixels to one azimuth pixel if multilook == 1 % define size of output image output_image=zeros(ceil(size_azimuth/ml_factor),size_range); % Dummy index index=1; % Spatial averaging for i=1:ml_factor:size_azimuth-ml_factor % jump along azimuth axis according to multilooking factor vek=processed(i:i+(ml_factor-1),:); % select azimuth bins m_vek=mean(abs(vek),1); % average value of azimuth bins output_image(index,:)=m_vek; index=index+1; end % Final SAR image (multi-looked) processed = output_image; end %-------------------------------------------------------------------------- % H.) Display SAR image figure; imagesc(abs(processed));colormap('gray') title('Processed SAR image') xlabel('Range','FontSize',12); ylabel('Azimuth','FontSize',12); caxis([0 max_power]); axis equal; axis off; %--------------------------------------------------------------------------