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1、functionJPDAF(target_position,n,T,MC_number,c)%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%程序功能:采用JPDA数据关联算法实现两个个匀速运动目标的点迹与航迹的关联%输入变量:%-target_position:目标的初始位置%-n:采样次数%-T:采样间隔%-MC_number:仿真次数%-c:目标个数%输出变量:%无%参考文献:%黄玲,数据挖掘及融合技术研究与应用,西北工业大学硕士学位论文,2004年%声明：%该代码为作者毕业设计内容，鉴于学术交流的角度，现在
2、公开发布该代码%该代码非本人原创，修改自网上另一位作者的JPDA代码%该代码仅用于学术交流，请勿用于任何其它商业用途，请大家自觉遵守%如果有人用该代码进行不合适的用途，该代码作者不承担任何责任%请遵守作者的劳动成果，转载请标明%作者邮箱：%wangzexun@gmail.com%%%%%%%%%%%%%%%%%%%%%%%%%%参数定义%%%%%Pd=1;%检测概率Pg=0.99;%正确量测落入跟踪门内得概率g_sigma=9.21;%门限lambda=2;gamma=lambda*10^(-6);%每一个单位面积(km^2)内产生lambda个杂波Targe
3、t_measurement=zeros(c,2,n);%目标观测互联存储矩阵target_delta=[100100];%目标对应的观测标准差P=zeros(4,4,c);%协方差矩阵P1=[target_delta(1)^2000;00.0100;00target_delta(1)^20;0000.01];%初始协方差矩阵P(:,:,1)=P1;P(:,:,2)=P1;A=[1T00;0100;001T;0001];%状态转移矩阵C=[1000;0010];%观测矩阵R=[target_delta(1)^20;0target_delta(1)^2];%观测协
4、方差矩阵Q=[40;04];%系统过程噪声协方差G=[T^2/20;T0;0T^2/2;0T];%过程噪声矩阵x_filter=zeros(4,c,n);%存储目标的各时刻的滤波值x_filter1=zeros(4,c,n,MC_number);%MC_number次MontleCarlo仿真所得全部结果存储矩阵data_measurement=zeros(c,2,n);%观测存储矩阵data_measurement1=zeros(c,4,n);%实际位置坐标x,y矩阵%%%%%%%%产生目标的实际位置%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
5、%%%data_measurement1(:,:,1)=target_position;%实际位置矩阵初始化fori=1:cforii=2:n%实际位置data_measurement1(i,:,ii)=(A*data_measurement1(i,:,ii-1)')'+(G*sqrt(Q)*(randn(2,1)))';endenda=zeros(1,n);b=zeros(1,n);fori=1:na(i)=data_measurement1(1,1,i);b(i)=data_measurement1(1,3,i);endplot(a,b,'b-');hol
6、don;a=zeros(1,n);b=zeros(1,n);fori=1:na(i)=data_measurement1(2,1,i);b(i)=data_measurement1(2,3,i);endplot(a,b,'r-');xlabel('x(m)'),ylabel('y(m)');legend('目标a的实际位置','目标b的实际位置',1);grid;%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%程序主体%%%%%%%%%%%%%%%%%%%%%%forM=1:MC_number%%%%%%%%%%%%%%%%%%%%
7、%%%1.产生路径%%%%%%%%%%%%%%%%%%%%%%%Noise=[];fori=1:nforj=1:c%各传感器观测的位置data_measurement(j,1,i)=data_measurement1(j,1,i)+rand(1)*target_delta(j);data_measurement(j,2,i)=data_measurement1(j,3,i)+rand(1)*target_delta(j);endend%%%%%%%%%%%%%%%%%%%%%%%%%%2.产生杂波,并确定有效观测%%%%%%%%%%%%%%%%%%%%%%%%
8、%%%%%S=zeros(2,2,c)
