【WSN定位】基于非测距的定位算法Dv-Hop算法实现二维和三维节点定位附matlab代码

% BorderLength-----正方形区域的边长，单位：m% NodeAmount------网络节点的总个数% BeaconAmount---信标节点数% UNAmount--------未知节点数% Sxy-----------------用于存储节点的序号，横坐标，纵坐标的矩阵% Beacon------------信标节点坐标矩阵% UN-----------------未知节点坐标矩阵% Distance-----------未知节点到信标节点距离矩阵 % X------------------未知节点估计坐标初始矩阵% R------------------节点的通信距离，一般为10-100mclear,close all;BorderLength=100;%正方形区域的边长NodeAmount=100;%网络节点的总个数BeaconAmount=10;UNAmount=NodeAmount-BeaconAmount;R=50;Dall=zeros(NodeAmount,NodeAmount,NodeAmount); %距离初始矩阵h=zeros(NodeAmount,NodeAmount,NodeAmount); %初始跳数矩阵X=zeros(2,UNAmount,NodeAmount); %未知节点估计坐标初始矩阵%~~~~~~~~~在正方形区域内产生均匀分布的随机拓扑~~~~~~~~~~~~~~~site=BorderLength.*rand(2,NodeAmount); %随机产生节点坐标Sxy=[1:NodeAmount;site]; %带序号的节点坐标Beacon=[Sxy(2,1:BeaconAmount);Sxy(3,1:BeaconAmount)]; %信标节点坐标UN=[Sxy(2,(BeaconAmount+1):NodeAmount);Sxy(3,(BeaconAmount+1):NodeAmount)]; %未知节点坐标%~~~~~~~~画出节点分布图~~~~~~~~~~~~~~~~~figure(1)plot(Sxy(2,1:BeaconAmount),Sxy(3,1:BeaconAmount),'r*',Sxy(2,(BeaconAmount+1):NodeAmount),Sxy(3,(BeaconAmount+1):NodeAmount),'k.')xlim([0,BorderLength]);ylim([0,BorderLength]); title('红色*表示信标节点  黑色.表示未知节点')endA=2*(a'); %'表示求矩阵的转置B=zeros(BeaconAmount-1,1); for m=1:UNAmount      for i=1:(BeaconAmount-1)       B(i,1)=d(BeaconAmount,m)^2-d(i,m)^2+Beacon(1,i)^2-Beacon(1,BeaconAmount)^2+Beacon(2,i)^2-Beacon(2,BeaconAmount)^2; %B=b矩阵     end           X1=inv(A'*A)*A'*B; %inv表示求矩阵的逆矩阵           X(1,m)=X1(1,1);           X(2,m)=X1(2,1);   %将求得的未知节点的坐标依次存入X矩阵 end error=zeros(1,UNAmount); %未知节点的定位误差 for i=1:UNAmounterror(i)=(((X(1,i)-UN(1,i))^2+(X(2,i)-UN(2,i))^2)^0.5); %每个未知节点的定位误差 endfigure(2)stem(error)xlabel('未知节点序号')title('每个未知节点的误差') Berror=sum(error)/UNAmount  %平均定位误差 Accuracy= Berror /R  %定位精确度