WSN定位蒙特卡洛方法MCL的MATLAB实现源码

1、clear;clc;%初始化工作Ns = 20;Nn = 200;Vmax = 20;Xrange = 200;Yrange = 200;tr = 50;step = 20;N = 20;Nf = 3; %采样盒子确定时，估计位置要扩大圆面积ns_range = 200; %每个采样盒子的最大采样次数for i = 1:Ns Xseed(1,i)=rand(1,1)*Xrange; Yseed(1,i)=rand(1,1)*Yrange;endfor i = 1:Nn Xnode(1,i)=rand(1,1)*Xrange; Ynode(1,i)=rand(1,1)*Yrange; Xnode

2、_g(1,i)=Xnode(1,i); %MCL估计位置,初始值设置为真实位置 Ynode_g(1,i)=Ynode(1,i);end%初始时刻的粒子群，for every nodefor i = 1:Nn for j = 1:N lx(i,j,1) = Xnode_g(1,i); ly(i,j,1) = Ynode_g(1,i); endend%figure(1);%plot(Xseed,Yseed,bo,Xnode,Ynode,k*);%节点们开始运动，每次定位完成才开始下一次运动，这里假设这个定位过程耗时非常短%仿真步数for k=2:step %新的时刻，节点们先运动一下,RWP模型

3、for i = 1:Ns r = rand(1,1)*Vmax; thita = rand(1,1)*2*pi; Xseed(k,i) = Xseed(k-1,i) + r*cos(thita); if Ynode(k,i) Yrange | Ynode(k,i) 0 Xnode(k,i) = Xnode(k-1,i) + r*cos(thita); Ynode(k,i) = Ynode(k-1,i) - r*sin(thita); end end %对每一个node逐个进行定位 for i = 1:Nn %测试每个seed是否可以用来定位 A1 = ; %存储1跳锚节点序号 A2 = ; %

4、存储2跳锚节点序号 for j = 1:Ns d1 = sqrt(Xnode(k,i)-Xseed(k,j)2+(Ynode(k,i)-Yseed(k,j)2); if d1tr & d1=2*tr for m = 1:Nn if m = i dmi = sqrt(Xnode(k,i)-Xnode(k,m)2+(Ynode(k,i)-Ynode(k,m)2); dms = sqrt(Xnode(k,m)-Xseed(k,j)2+(Ynode(k,m)-Yseed(k,j)2); if dmi=tr & dms=tr A2 = A2 j; end end end end end %接下来要获取采

5、样盒子，每个粒子都要有一个采样盒子，然后还要进行采样，每个采样盒子的采样都要有一个次数限制，这里还是要分四种情况 temp1 = size(A1,2); temp2 = size(A2,2); %第一种情况 if temp1=0 & temp2=0 Xnode_g(k,i)=Xnode_g(k-1,i); Ynode_g(k,i)=Ynode_g(k-1,i); for j = 1:N lx(i,j,k) = 0; %周围没有锚节点，没法进行定位，则粒子群全部置零 ly(i,j,k) = 0; end end %第二种情况 if temp1=0 & temp2=0 for j = 1:N sa

6、mbox1 = Xnode_g(k-1,i)-Nf*Vmax; sambox2 = Xnode_g(k-1,i)+Nf*Vmax; sambox3 = Ynode_g(k-1,i)-Nf*Vmax; sambox4 = Ynode_g(k-1,i)+Nf*Vmax; Xsambox_min(i,j,k) = max(sambox1); Xsambox_max(i,j,k) = min(sambox2); Ysambox_min(i,j,k) = max(sambox3); Ysambox_max(i,j,k) = min(sambox4); %从采样盒子里采样 lx(i,j,k) = unif

7、rnd(Xsambox_min(i,j,k),Xsambox_max(i,j,k),1,1); ly(i,j,k) = unifrnd(Ysambox_min(i,j,k),Ysambox_max(i,j,k),1,1); ns = 1; %滤波 and = ; for m = 1:temp1 d1(m) = sqrt(lx(i,j,k)-Xseed(k,A1(m)2+(ly(i,j,k)-Yseed(k,A1(m)2); end end ns = ns+1; end %进行最终的判断 and = ; for m = 1:temp1 d1(m) = sqrt(lx(i,j,k)-Xseed(k

8、,A1(m)2+(ly(i,j,k)-Yseed(k,A1(m)2); if d1(m)tr and = and 1; end end if sum(and)=0 lx(i,j,k) = 0; ly(i,j,k) = 0; end end %至此 节点 i 的粒子群已经得到 %下面是进行定位，粒子群的优化 num_zero = 0; for j = 1:N if lx(i,j,k) = 0 num_zero = num_zero+1; end end %k时刻的定位位置 if num_zero = N Xnode_g(k,i) = Xnode_g(k-1,i); Ynode_g(k,i) =

9、Ynode_g(k-1,i); end if num_zero = N Xnode_g(k,i) = sum(lx(i,:,k)/(N-num_zero); Ynode_g(k,i) = sum(ly(i,:,k)/(N-num_zero); end %粒子群补全N个 if num_zero = N for j = 1:N lx(i,j,k) = 0; ly(i,j,k) = 0; end end if num_zero = N for j = 1:N if lx(i,j,k) = 0 lx(i,j,k) = Xnode_g(k,i); ly(i,j,k) = Ynode_g(k,i); en

10、d end end end %第三种情况 if temp1=0 & temp2=0 for j = 1:N sambox1 = Xnode_g(k-1,i)-Nf*Vmax; sambox2 = Xnode_g(k-1,i)+Nf*Vmax; sambox3 = Ynode_g(k-1,i)-Nf*Vmax; sambox4 = Ynode_g(k-1,i)+Nf*Vmax; Xsambox_min(i,j,k) = max(sambox1); Xsambox_max(i,j,k) = min(sambox2); Ysambox_min(i,j,k) = max(sambox3); Ysamb

11、ox_max(i,j,k) = min(sambox4); and = and 0; else and = and 1; end end ns = ns+1; end %进行最终的判断 and = ; for m = 1:temp2 d1(m) = sqrt(lx(i,j,k)-Xseed(k,A2(m)2+(ly(i,j,k)-Yseed(k,A2(m)2); if d1(m)tr & d1(m)=2*tr and = and 0; else and = and 1; end end if sum(and)=0 lx(i,j,k) = 0; ly(i,j,k) = 0; end end %至

12、此 节点 i 的粒子群已经得到 %下面是进行定位，粒子群的优化 num_zero = 0; for j = 1:N if lx(i,j,k) = 0 num_zero = num_zero+1; end end %k时刻的定位位置 if num_zero = N Xnode_g(k,i) = Xnode_g(k-1,i); Ynode_g(k,i) = Ynode_g(k-1,i); end if num_zero = N Xnode_g(k,i) = sum(lx(i,:,k)/(N-num_zero); Ynode_g(k,i) = sum(ly(i,:,k)/(N-num_zero);

13、end %粒子群补全N个 if num_zero = N for j = 1:N lx(i,j,k) = 0; ly(i,j,k) = 0; end end if num_zero = N for j = 1:N if lx(i,j,k) = 0 lx(i,j,k) = Xnode_g(k,i); ly(i,j,k) = Ynode_g(k,i); end end end end %第四种情况 if temp1=0 & temp2=0 for j = 1:N sambox1 = Xnode_g(k-1,i)-Nf*Vmax; sambox2 = Xnode_g(k-1,i)+Nf*Vmax;

14、sambox3 = Ynode_g(k-1,i)-Nf*Vmax; sambox4 = Ynode_g(k-1,i)+Nf*Vmax; Xsambox_min(i,j,k) = max(sambox1); Xsambox_max(i,j,k) = min(sambox2); Ysambox_min(i,j,k) = max(sambox3); Ysambox_max(i,j,k) = min(sambox4); %从采样盒子里采样 lx(i,j,k) = unifrnd(Xsambox_min(i,j,k),Xsambox_max(i,j,k),1,1); ly(i,j,k) = unifrn

15、d(Ysambox_min(i,j,k),Ysambox_max(i,j,k),1,1); ns = 1; %滤波 and = ; for m = 1:temp1 d1(m) = sqrt(lx(i,j,k)-Xseed(k,A1(m)2+(ly(i,j,k)-Yseed(k,A1(m)2); if d1(m)=tr and = and 0; end if d1(m)tr and = and 1; end d1(m) = sqrt(lx(i,j,k)-Xseed(k,A2(m)2+(ly(i,j,k)-Yseed(k,A2(m)2); if d1(m)tr & d1(m)=2*tr and = and 0; else and = and 1; end end if sum(and)=0 lx(i,j,k) = 0; ly(i,j,k) = 0; end end %至此 节点 i 的粒子群已经得到 %下面是进行定位，粒子群的优化 num_zero = 0; for j = 1:N if lx(i,j,k) = 0 num_zero = num_zero+1; end end %k时刻的定位位置 if num_zero = N Xnode_g(k,i) = Xnode_g(k-1,i); Ynode_g(k,i) = Ynode_g(k-1,i); end if num_z