GPS和INS联合导航matlab程序（带数据有用的）.zip.zip

%GPS/INS无反馈位置组合 卡尔曼滤波器 %%%%%%%%%%%%%%%%%% %edit by horsejun %%%%%%%%%%%%%%%%%% %每秒更新一次速度位置误差 %连续状态系统方程 %dx = F*x + G*w %z = H*x + v %离散状态系统方程 %x(k+1) = A*x(k) + B*w(k) %z(k+1) = C*x(k+1) + v(k+1) function [E_attitude, E_velocity, E_position, PP] = kalman_GPS_INS_position_sp_NFb(Dp, v, p, quat, Fn, Q, R, Tg, Ta, tao) %输入 %Dp 量测位置误差， 作为滤波器输入, %Dv 量测速度误差， 作为滤波器输入， %p ins输出位置，作为滤波器系统参数 %v ins输出速度，作为滤波器系统参数 %fn ins输出导航系下比力，作为滤波器参数 %quat ins输出四元数，作为滤波器参数 %Q 系统噪声方差 %R 测量噪声方差 %Ta 加表误差漂移相关时间 %Tg 陀螺仪误差漂移相关时间 %tao 迭代步长 %%%%%%%输入向量均为行向量%%%%%%%%%%%%% %输出 %E_position 位置预测值 %E-velocity 速度预测值 %各参数初始化 Re = 6378245; %地球长半径 e = 1/298.257; %地球扁率 wie = 7.292e-5; %地球自转角速度 % 东北天速度 Ve0 = v(:,1); Vn0 = v(:,2); Vu0 = v(:,3); % 导航位置 L0 = p(:,1); h0 = p(:,3); %卡尔曼滤波参数初始化 PP(1:18,1:18) = diag([1/(36*57) 1/(36*57) 1/57, 0.0001 0.0001 0.0001, 0 0 1, 0.1/(57*3600) 0.1/(57*3600) 0.1/(57*3600), 0.04/(57*3600) 0.04/(57*3600) 0.04/(57*3600), 1e-4 1e-4 1e-4].^2); %初始误差协方差阵 PP0 = PP; X = zeros(18,1); %初始状态 E_attitude = zeros(1,3); E_position = zeros(1,3); E_velocity = zeros(1,3); n = size(Dp,1); for i=1:n-1 %参数赋值 Ve = Ve0(i); Vn = Vn0(i); Vu = Vu0(i); L = L0(i); h = h0(i); fe = Fn(i,1); fn = Fn(i,2); fu = Fn(i,3); Rm = Re*(1-2*e+3*e*sin(L)^2); Rn = Re*(1-e*sin(L)^2); %由四元数计算姿态阵 q = quat(i,:); Cnb = [1-2*(q(3)^2+q(4)^2), 2*(q(2)*q(3)-q(1)*q(4)), 2*(q(2)*q(4)+q(1)*q(3)); 2*(q(2)*q(3)+q(1)*q(4)), 1-2*(q(2)^2+q(4)^2), 2*(q(3)*q(4)-q(1)*q(2)); 2*(q(2)*q(4)-q(1)*q(3)), 2*(q(3)*q(4)+q(1)*q(2)), 1-2*(q(2)^2+q(3)^2)]; %连续系统状态转换阵 F 的时间更新 F = zeros(18,18); F(1,2) = wie*sin(L)+Ve*tan(L)/(Rn+h); F(1,3) = -(wie*cos(L)+Ve/(Rn+h)); F(1,5) = -1/(Rm+h); F(1,9) = Vn/(Rm+h)^2; F(2,1) = -(wie*sin(L)+Ve*tan(L)/(Rn+h)); F(2,3) = -Vn/(Rm+h); F(2,4) = 1/(Rn+h); F(2,7) = -wie*sin(L); F(2,9) = -Ve/(Rn+h)^2; F(3,1) = wie*cos(L)+Ve/(Rn+h); F(3,2) = Vn/(Rm+h); F(3,4) = tan(L)/(Rn+h); F(3,7) = wie*cos(L)+Ve*(sec(L)^2)/(Rn+h); F(3,9) = -Ve*tan(L)/(Rn+h)^2; F(4,2) = -fu; F(4,3) = fn; F(4,4) = Vn*tan(L)/(Rm+h)-Vu/(Rm+h); F(4,5) = 2*wie*sin(L)+Ve*tan(L)/(Rn+h); F(4,6) = -(2*wie*cos(L)+Ve/(Rn+h)); F(4,7) = 2*wie*cos(L)*Vn+Ve*Vn*sec(L)^2/(Rn+h)+2*wie*sin(L)*Vu; F(4,9) = (Ve*Vu-Ve*Vn*tan(L))/(Rn+h)^2; F(5,1) = fu; F(5,3) = -fe; F(5,4) = -2*(wie*sin(L)+Ve*tan(L)/(Rn+h)); F(5,5) = -Vu/(Rm+h); F(5,6) = -Vn/(Rm+h); F(5,7) = -(2*wie*cos(L)+Ve*(sec(L)^2)/(Rn+h))*Ve; F(5,9) = (Ve^2*tan(L)+Vn*Vu)/(Rn+h)^2; F(6,1) = -fn; F(6,2) = fe; F(6,4) = 2*(wie*cos(L)+Ve/(Rn+h)); F(6,5) = 2*Vn/(Rm+h); F(6,7) = -2*Ve*wie*sin(L); F(6,9) = -(Vn^2+Ve^2)/(Rn+h)^2; F(7,5) = 1/(Rm+h); F(7,9) = -Vn/(Rm+h)^2; F(8,4) = 1/((Rn+h)*cos(L)); F(8,7) = Ve*tan(L)/((Rn+h)*cos(L)); F(8,9) = -Ve/(cos(L)*(Rn+h)^2); F(9,6) = 1; F(1:3,10:12) = Cnb; F(1:3,13:15) = Cnb; F(4:6,16:18) = Cnb; F(13,13) = -1/Tg(1); F(14,14) = -1/Tg(2); F(15,15) = -1/Tg(3); F(16,16) = -1/Ta(1); F(17,17) = -1/Ta(2); F(18,18) = -1/Ta(3); %连续系统输入矩阵更新 G = zeros(18,9); G(1:3,1:3) = Cnb; G(13:15,4:6) = eye(3,3); G(16:18,7:9) = eye(3,3); %连续系统量测阵更新 H = zeros(3,18); H(1,7) = 1; H(2,8) = 1; H(3,9) = 1; %连续系统离散化 A = eye(18,18)+F*tao; B = (eye(18,18)+tao*F/2)*G*tao; %卡尔曼滤波 P = A*(PP0)*A'+B*Q*B'; K = P*H'*inv(H*P*H'+R); PP0 = (eye(18,18)-K*H)*P; PP0 = (PP0+PP0')/2; PP(i,:) = diag(PP0); z = Dp(i+1,:)'; XX = A*X+K*(z-H*A*X); X = XX; E_attitude(i+1,:) = XX(1:3)'; E_velocity(i+1,:) = XX(4:6)'; E_position(i+1,:) = XX(7:9)'; end