请你帮我编写能生成惯导和里程计的原始数据的MATLAB程序，要求数据真实可靠

对于惯导数据，需要模拟三轴陀螺仪和加速度计的输出。可以使用以下代码来模拟：

% Set up parameters
dt = 0.01; % Time step
t = 0:dt:10; % Time vector
gyro_bias = [0.01; 0.02; 0.03]; % Gyro bias
gyro_noise_sd = [0.01; 0.01; 0.01]; % Gyro noise standard deviation
accel_bias = [0.1; 0.1; 0.1]; % Accelerometer bias
accel_noise_sd = [0.01; 0.01; 0.01]; % Accelerometer noise standard deviation

% Initialize values
gyro = zeros(3,length(t));
accel = zeros(3,length(t));
gyro(:,1) = [0.1; -0.2; 0.3];
accel(:,1) = [0; 0; 9.81];

% Generate data
for i = 2:length(t)
    % Simulate gyro output
    gyro(:,i) = gyro(:,i-1) + dt*(gyro_bias + randn(3,1).*gyro_noise_sd);
    
    % Simulate accelerometer output
    accel(:,i) = R(:,i-1)*accel(:,i-1) + [0; 0; 9.81] + accel_bias + randn(3,1).*accel_noise_sdi);
end

其中，`gyro_bias`和`gyro_noise_sd`分别是陀螺仪的偏差和噪声标准差，`accel_bias`和`accel_noise_sd`分别是加速度计的偏差和噪声标准差。`R`是一个旋转矩阵，用于将加速度计的输出转换为惯性坐标系下的加速度。

对于里程计数据，可以使用以下代码来模拟：

% Set up parameters
dt = 0.01; % Time step
t = 0:dt:10; % Time vector
wheel_radius = 0.3; % Wheel radius
wheel_base = 1; % Wheelbase
encoder_resolution = 1000; % Encoder resolution
encoder_noise_sd = 0.1; % Encoder noise standard deviation

% Initialize values
x = zeros(3,length(t));
x(:,1) = [0; 0; pi/4]; % Initial position and orientation

% Generate data
for i = 2:length(t)
    % Simulate forward and angular velocity
    V = 2 + i*dt; % Forward velocity
    omega = pi/4; % Angular velocity
    
    % Simulate encoder readings
    dL = V*dt + randn()*encoder_noise_sd; % Left wheel displacement
    dR = V*dt + randn()*encoder_noise_sd; % Right wheel displacement
    
    % Calculate robot motion
    dS = (dL + dR)/2; % Robot displacement
    dTheta = (dR - dL)/wheel_base; % Robot orientation change
    dx = dS*cos(x(3)+dTheta/2); % x coordinate change
    dy = dS*sin(x(3)+dTheta/2); % y coordinate change
    
    % Update robot pose
    x(:,i) = x(:,i-1) + [dx; dy; dTheta];
end

其中，`wheel_radius`和`wheel_base`分别是轮子的半径和轮距，`encoder_resolution`是编码器的分辨率，`encoder_noise_sd`是编码器的噪声标准差。`dL`和`dR`分别是左轮和右轮的位移，根据这两个值可以计算出机器人的位移和方向变化，并更新机器人的位置和姿态。