/// <summary>
/// 生产平差器
/// </summary>
/// <param name="type"></param>
/// <returns></returns>
public static MatrixAdjuster Create(AdjustmentType type)
{
MatrixAdjuster Adjustment = null;
switch (type)
{
case AdjustmentType.参数平差:
Adjustment = new ParamAdjuster();
break;
case AdjustmentType.条件平差:
Adjustment = new ConditionalAdjuster();
break;
case AdjustmentType.具有参数的条件平差:
Adjustment = new ConditionalAdjusterWithParam();
break;
case AdjustmentType.具有条件的参数平差:
Adjustment = new ParamAdjusterWithCondition();
break;
case AdjustmentType.卡尔曼滤波:
Adjustment = new SimpleKalmanFilter();
// Adjustment = new KalmanFilter();
break;
case AdjustmentType.均方根滤波:
Adjustment = new SquareRootInformationFilter();
break;
case AdjustmentType.序贯平差:
Adjustment = new SequentialAdjuster();
break;
case AdjustmentType.参数加权平差:
Adjustment = new WeightedParamAdjuster();
break;
case AdjustmentType.递归最小二乘:
Adjustment = new RecursiveAdjuster();
break;
case AdjustmentType.单期递归最小二乘:
Adjustment = new SingleRecursiveAdjuster();
break;
default:
//Adjustment = new ParamAdjuster();
break;
}
if (Adjustment == null)
{
throw new Exception("尚未实现 " + type);
}
return(Adjustment);
}
/// <summary>
/// 滤波
/// </summary>
/// <param name="newVal"></param>
/// <returns></returns>
public RmsedNumeral Filter(RmsedNumeral newVal)
{
var builder = new OneDimAdjustMatrixBuilder(newVal, PrevAdjustment);
var sp = new SimpleKalmanFilter();
var a = sp.Run(builder);
var est = a.Estimated;
this.PrevAdjustment = a;//update
return(new RmsedNumeral(est[0], est.GetRmsVector()[0]));
}
/// <summary>
/// 水平Kalman滤波
/// </summary>
/// <param name="val"></param>
/// <returns></returns>
private double DoLevelKalmanFilter(double val)
{
var builder = new OneDimAdjustMatrixBuilder(val, Adjustment);
var sp = new SimpleKalmanFilter();
Adjustment = sp.Run(builder);
var smoothData = Adjustment.Estimated[0];
return(smoothData);
}
/// <summary>
/// 滤波。默认期望为常数。
/// </summary>
/// <param name="rawValue"></param>
/// <returns></returns>
protected double Filter(double rawValue)
{
AdjustResultMatrix prev = CurrentAdjustment;
var builder = new OneDimAdjustMatrixBuilder(rawValue, prev);
var sp = new SimpleKalmanFilter();
var ad = sp.Run(builder);
CurrentAdjustment = ad;
var smoothData = ad.Estimated[0];
return(smoothData);
}
