MATLAB代做|FPGA代做|python代做-SAAC-CFAR目标检测源码

function  cid =  SAACCFAR( data , alarm, winSize, strip, cenSize) 
% Using to Constant False Alarm based on Gaussian distribution 
% input: 
%         data     data channel                      uint/double 
%         alarm    Constant Flase Alarm              uint/double 
%         winSize  Size of the protective area(half) uint/double 
%         strip    Size of strip area                uint/double 
%         cenSize  Size of the target area(half)     uint/double  
% output: 
%         cid     0/1(1 stand for the target)    byte   
% form  : 
%         cid =  SAACCFAR( data , alarm, winSize, strip, cenSize) 
% edited: 2011-04-28 by liujie  SPL@WHU 
 
%% function Body 
 
% ���Է��Ŷ��� 
DEBUG = 1; 
 
%ͨ���龯�ʼ�����ֵ 
threshold = norminv(1-alarm); 
 
[row col] = size(data); 
 
cid = zeros(row,col); 
center_data = zeros((2.*cenSize+1).*(2.*cenSize+1),1); 
clutter_data = zeros(4.*strip.*strip+4.*strip.*(2.*winSize+1),1); 
clutter_top = zeros(strip.*(2.*strip+2.*winSize+1),1); 
clutter_buttom = zeros(strip.*(2.*strip+2.*winSize+1),1); 
clutter_left = zeros(strip.*(2.*winSize+1),1); 
clutter_right = zeros(strip.*(2.*winSize+1),1); 
 
num1 = strip.*(2.*strip+2.*winSize+1); 
num2 = strip.*(2.*winSize+1); 
num3 = strip+winSize; 
num4 = 4.*strip.*strip+4.*strip.*(2.*winSize+1); 
num5 = (2.*cenSize+1).*(2.*cenSize+1); 
 
for p = (winSize+strip+1) : (row- winSize-strip) 
    for q = (winSize+strip+1) : (col- winSize-strip) 
         
        %��ö������������� 
        clutter_top = reshape(data(p-num3:p-winSize-1,q-num3:q+num3),[num1,1]); 
         
        %��õײ����������� 
        clutter_buttom = reshape(data(p+winSize+1:p+num3,q-num3:q+num3),[num1,1]); 
         
        %���������������� 
        clutter_left = reshape(data(p-winSize:p+winSize,q-num3:q-winSize-1),[num2,1]); 
         
        %����ұ����������� 
        clutter_right = reshape(data(p-winSize:p+winSize,q+winSize+1:q+num3),[num2,1]); 
        
        %����Ӳ����� 
        clutter_data = cat(1,clutter_top,clutter_buttom,clutter_left,clutter_right); 
SAAC_data = zeros(size(clutter_data)); 
SAAC_data(1) = clutter_data(1);  
SAAC_data(2) = clutter_data(2); 
SAAC_mean=mean(SAAC_data(1:2)); 
SAAC_var=var(double(SAAC_data(1:2))); 
for sh=3:num4 
    if abs(clutter_data(sh)-SAAC_mean)<SAAC_var 
SAAC_data(sh)=clutter_data(sh) ; 
 
% ͳ�Ʒ�����Ӳ�ֵ 
x = SAAC_data(find(SAAC_data(:)~=0)); 
 
SAAC_mean=mean(x(:)); 
SAAC_var=var(double(x(:))); 
    end 
end 
 
         
        %���Ŀ���������� 
        center_data = reshape(data(p-cenSize:p+cenSize,q-cenSize:q+cenSize),[num5,1]); 
         
        %����Ӳ������ֵ 
        clutter_mean = mean(clutter_data(:)); 
         
        %����Ӳ����򷽲� 
        clutter_var = sqrt(var(double(clutter_data(:)))); 
         
        %���Ŀ�������ֵ 
        center_mean = mean(center_data(:)); 
         
        %�ж��Ƿ�ΪĿ������ 
  T = SAAC_var.*threshold+SAAC_mean; 
   % T=clutter_var.*sqrt(-2*log(alarm)) ; 
         if center_mean >= T 
             
             for ii = p-cenSize:p+cenSize 
                 for jj = q-cenSize:q+cenSize 
                     cid(ii,jj) =1;  
                 end 
             end 
              
        end 
         
    end 
end ...end of p iteration 
     
if DEBUG 
    figure; imshow(cid,[0 1]); 
end 
  
end... end of function 

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