C#实现卡尔曼滤波算法 输入List<double>返回List<double>

可以使用以下代码来实现卡尔曼滤波算法：

using MathNet.Numerics.LinearAlgebra;
using MathNet.Numerics.LinearAlgebra.Double;

public List<double> KalmanFilter(List<double> measurements)
{
    // 初始化卡尔曼滤波器参数
    double initialEstimate = measurements[0];
    double initialError = 1;
    double processNoise = 0.1;
    double measurementNoise = 1;
    
    // 创建状态转移矩阵
    var stateTransitionMatrix = DenseMatrix.OfArray(new double[,] { { 1 } });
    
    // 创建控制输入矩阵
    var controlInputMatrix = DenseMatrix.OfArray(new double[,] { { 0 } });
    
    // 创建测量矩阵
    var measurementMatrix = DenseMatrix.OfArray(new double[,] { { 1 } });
    
    // 创建过程噪声协方差矩阵
    var processNoiseCovariance = DenseMatrix.OfArray(new double[,] { { processNoise } });
    
    // 创建测量噪声协方差矩阵
    var measurementNoiseCovariance = DenseMatrix.OfArray(new double[,] { { measurementNoise } });
    
    // 创建初始状态估计向量
    var initialStateEstimate = DenseVector.OfArray(new double[] { initialEstimate });
    
    // 创建初始误差协方差矩阵
    var initialErrorCovariance = DenseMatrix.OfArray(new double[,] { { initialError } });
    
    // 创建卡尔曼滤波器
    var kalmanFilter = new KalmanFilter(stateTransitionMatrix, controlInputMatrix, measurementMatrix,
                                        processNoiseCovariance, measurementNoiseCovariance,
                                        initialStateEstimate, initialErrorCovariance);
    
    // 存储滤波结果
    var filteredMeasurements = new List<double>();
    
    // 运行卡尔曼滤波
    foreach (var measurement in measurements)
    {
        kalmanFilter.Predict();
        kalmanFilter.Correct(DenseVector.OfArray(new double[] { measurement }));
        
        filteredMeasurements.Add(kalmanFilter.State[0]);
    }
    
    return filteredMeasurements;
}