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clc;

clear all;

tic;

%data = csvread(‘G:\桌面文件\chuanganqi.csv’,2,5,[2 5 2000 5]);

%X = csvread(‘G:\桌面文件\chuanganqi.csv’,2,5,[2 5 2000 5]);

X = csvread(‘G:\桌面文件\chuanganqi.csv’,2,5);

%X = data(1:720000,1)*3600; %读取数据，以陀螺仪某一轴为例

%X = data(2:2000)*3600

Ts = 0.01; %采样时间

[N,M] = size(X);

N_max = floor(N/3);%（N/3）

T = zeros(N_max,10);

R = zeros(N_max,10);

for d = 1 %设置迭代的步长为d，当d=1时为传统的Allan方差

Allan = zeros(N_max,2);

Cluster_mean = zeros(N,1);

for n = 1:d:N_max %每一簇的簇长

K = floor(N/n);

for k = 1:K

Cluster_mean(k,1) = mean(X((n*(k-1)+1):(n

k),1));

end

Cluster_diff = diff(Cluster_mean(1:K),1);

Allan(n,1) = n

Ts; %Time tau

Allan(n,2) = sum((Cluster_diff.^2))/(2*(K-1));

end

Allan(any(Allan,2)==0,:)=[]

TUP = ceil(N_max/d);

RUP = ceil(N_max/d);

T(1:TUP,d)=Allan(:,1);

R(1:RUP,d)=Allan(:,2);

end

x1 = T(:,1);

y1 = R(:,1);

a= [1 2 3 4 5];%函数拟合过程

a(1:5)=lsqcurvefit(@test,a,x1,y1);

f=a(1)*x1.

^{(-2)+a(2)*x1.}

(-1)+a(3)*x1.

^(0)+a(4)*x1.

(1)+a(5)*x1.^(2);

figure(1)=figure(‘color’,[1 1 1]);

loglog(T(:,1),R(:,1),‘color’,[255/255,215/255,0/255]);

hold on;

loglog(x1, f,‘r’,‘LineWidth’,1.3);

hold on;

xlabel(‘Cluster Time （sec）’);

ylabel(‘Allan Deviation （deg/h）’);

grid on;

legend(’ Step size=1’,’ Step size=2’,’ Step size=3’,’ Fitting Curve’)

toc;

test

function f=test(a,x)

f=a(1)*x.

^(-2)+a(2)*x.

(-1)+a(3)*x.

^(0)+a(4)*x.

(1)+a(5)*x.^(2);

end