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ParticleFilter.m~
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ParticleFilter.m~
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%程序初始化操作%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
clc;
clear;
close all;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%全局变量定义%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
outdoor_sensor_data=370;
indoor_sensor_data=0;
sensor_data=outdoor_sensor_data+indoor_sensor_data;
d=0.1;%标准差
Theta=CreateGauss(0,d,1,sensor_data);%GPS航迹和DR航迹的夹角
ZOUT=zeros(4,outdoor_sensor_data);
ZIN=zeros(4,indoor_sensor_data);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%读取传感器数据%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
fgps=fopen('sensor_data_0415.txt','r');%%%打开文本
for n=1:sensor_data
gpsline=fgetl(fgps);%%%读取文本指针对应的行
if ~ischar(gpsline) break;%%%判断是否结束
end;
%%%%读取室内数据
time=sscanf(gpsline,'[Info] 2016-04-15%s(ViewController.m:%d)-[ViewController outputAccelertion:]:lat:%f;lon:%f;heading:%f;distance:%f;beacon_lat:%f;beacon_lon:%f');
data=sscanf(gpsline,'[Info] 2016-04-15 %*s (ViewController.m:%*d)-[ViewController outputAccelertion:]:lat:%f;lon:%f;heading:%f;distance:%f;beacon_lat:%f;beacon_lon:%f');
if(isempty(data))
break;
end
result=lonLat2Mercator(data(6,1),data(5,1));
gx(n)=result.X;%GPS经过坐标变换后的东向坐标,换算成米数
gy(n)=result.Y;%GPS经过坐标变换后的北向坐标,换算成米数
Phi(n)=(data(3,1)+90)*pi/180;%航向角
dd(n)=data(4,1);%某一周期的位移
ZIN(:,n)=[gx(n),gy(n),Phi(n),dd(n)];
end
fclose(fgps);%%%%%关闭文件指针
% 参数设置
N = 100; %粒子总数
Q = 5; %过程噪声
R = 5; %测量噪声
X = zeros(2, sensor_data); %存储系统状态
Z = zeros(2, sensor_data); %存储系统的观测状态
P = zeros(2, N); %建立粒子群
PCenter = zeros(2, sensor_data); %所有粒子的中心位置
w = zeros(N, 1); %每个粒子的权重
err = zeros(1,sensor_data); %误差
X(:, 1) = [ZIN(1,1); ZIN(2,1)]; %初始系统状态
Z(:, 1) = [ZIN(1,1); ZIN(2,1)] ; %初始系统的观测状态
cordinatex=round(ZIN(1,5));
cordinatey=round(ZIN(2,5));
%初始化粒子群
for i = 1 : N
P(:, i) = [randi([cordinatex-100,cordinatex+200],1);randi([cordinatey-200,cordinatey+100],1)];
dist = norm(P(:, i)-Z(:, 1)); %与测量位置相差的距离
w(i) = (1 / sqrt(R) / sqrt(2 * pi)) * exp(-(dist)^2 / 2 / R); %求权重
end
PCenter(:, 1) = sum(P, 2) / N; %所有粒子的几何中心位置
%%
err(1) = norm(X(:, 1) - PCenter(:, 1)); %粒子几何中心与系统真实状态的误差
% figure(1);
% set(gca,'FontSize',12);
% hold on
% plot(X(1, 1), X(2, 1), 'r.', 'markersize',30) %系统状态位置
% axis([cordinatex-100 cordinatex+200 cordinatey-200 cordinatey+100]),grid on;
% plot(P(1, :), P(2, :), 'k.', 'markersize',5); %各个粒子位置
% plot(PCenter(1, 1), PCenter(2, 1), 'b.', 'markersize',25); %所有粒子的中心位置
% legend('True State', 'Particles', 'The Center of Particles');
% title('Initial State');
% hold off
%%
%开始运动
for k = 2 : sensor_data
%模拟一个弧线运动的状态
X(:, k) = X(:, k-1) + 1 * [(sin( ZIN(3,k))); cos(ZIN(3,k))] ; %状态方程
Z(:, k) = ZIN(1:2, k) ; %观测方程
if ZIN(1,k) == 0
Z(:, k) = X(:, k); %观测方程
end
%粒子滤波
%预测
for i = 1 : N
P(:, i) = P(:, i) + 1 * [sin( ZIN(3,k)); cos( ZIN(3,k))] + wgn(2, 1, 10*log10(Q));
dist = norm(P(:, i)-Z(:, k)); %与测量位置相差的距离
w(i) = (1 / sqrt(R) / sqrt(2 * pi)) * exp(-(dist)^2 / 2 / R); %求权重
end
%归一化权重
wsum = sum(w);
for i = 1 : N
w(i) = w(i) / wsum;
end
%重采样(更新)
for i = 1 : N
wmax = 2 * max(w) * rand; %另一种重采样规则
index = randi(N, 1);
while(wmax > w(index))
wmax = wmax - w(index);
index = index + 1;
if index > N
index = 1;
end
end
P(:, i) = P(:, index); %得到新粒子
end
PCenter(:, k) = sum(P, 2) / N; %所有粒子的中心位置
%计算误差
err(k) = norm(X(:, k) - PCenter(:, k)); %粒子几何中心与系统真实状态的误差
% figure(2);
% set(gca,'FontSize',12);
% clf;
% hold on
% plot(X(1, k), X(2, k), 'r.', 'markersize',50); %系统状态位置
% axis([cordinatex-100 cordinatex+200 cordinatey-200 cordinatey+100]),grid on;
% plot(P(1, :), P(2, :), 'k.', 'markersize',5); %各个粒子位置
% plot(PCenter(1, k), PCenter(2, k), 'b.', 'markersize',25); %所有粒子的中心位置
% legend('True State', 'Particle', 'The Center of Particles');
% hold off
% pause(0.1);
end
%%
figure(3);
set(gca,'FontSize',12);
[groundtruthx,groundtruthy]=Groud_Truth();
plot(groundtruthx,groundtruthy,'r');hold on;
plot( ZIN(1,:), ZIN(2,:), '>');hold on;
plot(PCenter(1,:), PCenter(2,:), 'g');hold off;
axis([cordinatex-100 cordinatex+200 cordinatey-200 cordinatey+100]),grid on;
legend('真实轨迹','观测轨迹', '粒子滤波轨迹');
xlabel('x', 'FontSize', 20); ylabel('y', 'FontSize', 20);
axis equal;