Kalman Filter Implementation in C
The Kalman filter is an algorithm used to estimate system states, commonly applied in sensor data fusion and control systems. Below is a simple implementation example in the C programming language.
#include <stdio.h>
// 定义卡尔曼滤波参数
float Q = 0.1; // 过程噪声协方差
float R = 0.1; // 测量噪声协方差
// 初始化卡尔曼滤波器
float x_est = 0; // 估计值
float P_est = 1; // 估计协方差
// 更新卡尔曼滤波器
void update(float z) {
// 预测步骤
float x_pred = x_est;
float P_pred = P_est + Q;
// 更新步骤
float K = P_pred / (P_pred + R);
x_est = x_pred + K * (z - x_pred);
P_est = (1 - K) * P_pred;
}
int main() {
// 测量值
float z = 1;
// 更新卡尔曼滤波器
update(z);
// 打印估计值
printf("Estimated value: %f\n", x_est);
return 0;
}
In this example, we define the parameters and initializers of the Kalman filter, and implement a simple update function to update the Kalman filter. In the main function, we input a measurement value and call the update function to update the estimated value. Finally, we print out the estimated value.
Please note that this is just a simple example and in actual applications, there may be more complex parameter adjustments and data processing involved. If you need a more detailed implementation or want to learn more about Kalman filtering, it is recommended to consult academic literature or professional books.