在Android上实现JKalman

allprojects {
    repositories {
        ...
        maven { url 'https://jitpack.io' }
    }
}

dependencies {
    implementation 'com.github.mchapagai:JKalman:1.0.0'
}

import com.github.mchapagai.JKalmanFilter;

public class MainActivity extends AppCompatActivity {

    private JKalmanFilter kalmanFilter;

    @Override
    protected void onCreate(Bundle savedInstanceState) {
        super.onCreate(savedInstanceState);
        setContentView(R.layout.activity_main);

        kalmanFilter = new JKalmanFilter(4, 2);
    }
}

import org.ejml.data.DenseMatrix64F;

public class MainActivity extends AppCompatActivity {

    private JKalmanFilter kalmanFilter;

    @Override
    protected void onCreate(Bundle savedInstanceState) {
        super.onCreate(savedInstanceState);
        setContentView(R.layout.activity_main);

        kalmanFilter = new JKalmanFilter(4, 2);

        // 设置系统模型矩阵
        DenseMatrix64F F = new DenseMatrix64F(4, 4, true, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1);
        kalmanFilter.setF(F);

        // 设置观测模型矩阵
        DenseMatrix64F H = new DenseMatrix64F(2, 4, true, 1, 0, 0, 0, 1, 0, 0, 0);
        kalmanFilter.setH(H);
    }
}

import org.ejml.data.DenseMatrix64F;

public class MainActivity extends AppCompatActivity {

    private JKalmanFilter kalmanFilter;

    @Override
    protected void onCreate(Bundle savedInstanceState) {
        super.onCreate(savedInstanceState);
        setContentView(R.layout.activity_main);

        kalmanFilter = new JKalmanFilter(4, 2);

        // 设置系统模型矩阵
        DenseMatrix64F F = new DenseMatrix64F(4, 4, true, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1);
        kalmanFilter.setF(F);

        // 设置观测模型矩阵
        DenseMatrix64F H = new DenseMatrix64F(2, 4, true, 1, 0, 0, 0, 1, 0, 0, 0);
        kalmanFilter.setH(H);

        // 设置过程噪声协方差矩阵
        DenseMatrix64F Q = new DenseMatrix64F(4, 4, true, 0.01, 0, 0, 0, 0.01);
        kalmanFilter.setQ(Q);

        // 设置观测噪声协方差矩阵
        DenseMatrix64F R = new DenseMatrix64F(2, 2, true, 0.1, 0, 0, 0.1);
        kalmanFilter.setR(R);
    }
}

import org.ejml.data.DenseMatrix64F;

public class MainActivity extends AppCompatActivity {

    private JKalmanFilter kalmanFilter;

    @Override
    protected void onCreate(Bundle savedInstanceState) {
        super.onCreate(savedInstanceState);
        setContentView(R.layout.activity_main);

        kalmanFilter = new JKalmanFilter(4, 2);

        // 设置系统模型矩阵
        DenseMatrix64F F = new DenseMatrix64F(4, 4, true, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1);
        kalmanFilter.setF(F);

        // 设置观测模型矩阵
        DenseMatrix64F H = new DenseMatrix64F(2, 4, true, 1, 0, 0, 0, 1, 0, 0, 0);
        kalmanFilter.setH(H);

        // 设置过程噪声协方差矩阵
        DenseMatrix64F Q = new DenseMatrix64F(4, 4, true, 0.01, 0, 0, 0, 0.01);
        kalmanFilter.setQ(Q);

        // 设置观测噪声协方差矩阵
        DenseMatrix64F R = new DenseMatrix64F(2, 2, true, 0.1, 0, 0, 0.1);
        kalmanFilter.setR(R);

        // 设置初始状态
        DenseMatrix64F x = new DenseMatrix64F(4, 1, true, 0, 0, 0, 0);
        kalmanFilter.setX(x);

        // 设置初始输出协方差矩阵
        DenseMatrix64F P = new DenseMatrix64F(4, 4, true, 1, 0, 0, 0, 1);
        kalmanFilter.setP(P);

        // 使用JKalman滤波器进行滤波
        DenseMatrix64F z = new DenseMatrix64F(2, 1, true, 10, 20);
        kalmanFilter.predict();
        kalmanFilter.update(z);
        DenseMatrix64F xPost = kalmanFilter.getX();
    }
}