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.

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