/// <summary>
/// 增加一个
/// </summary>
/// <param name="time"></param>
/// <param name="rawRange"></param>
/// <param name="rawPhaseRange"></param>
public SmoothRangeWindowOld Add(Time time, double rawRange, double rawPhaseRange, double ionoDiffer)
{ //通过是否相等，判断是否重复设值
if (CurrentData.PseudoRange == rawRange && this.CurrentData.PhaseRange == rawPhaseRange)
{
return(this);
}
this.CurrentData = new RangePhasePair(rawRange, rawPhaseRange, ionoDiffer)
{
Time = time
};
this.Add(time, CurrentData);
//电离层改正数据
if (IsDeltaIonoCorrect && SmoothRangeType == SmoothRangeSuperpositionType.快速更新算法)
{
double y = CurrentData.GetRawIonoAndHalfAmbiValue();//.RangeMinusPhase / 2;
IonoWindow.Add(time, y);
// BigIonoWindow.Add(time, y);
}
if (IsDeltaIonoCorrect)
{
var fit = IonoWindow.GetPolyFitValue(CurrentData.Time, OrderOfDeltaIonoPolyFit, IonoFitDataCount);
if (fit != null)
{
CurrentData.FittedIonoAndAmbiValue = fit.Value;
}
else
{
CurrentData.FittedIonoAndAmbiValue = CurrentData.GetRawIonoAndHalfAmbiValue();
}
}
return(this);
}
/// <summary>
/// 计算平滑的伪距，最快的迭代，带电离层的递推平滑算法，可以大大加快速度。
/// 算法已验证，和窗口单独迭代相同，需要注意的式如果正式平滑时，则不需要加权了。
/// 2018.06.20, czs， 这是推导了好几天才出的结果，并得到了验证，具体公式请参看本人发表的文章：**平滑伪距***。
/// </summary>
/// <returns></returns>
public RmsedNumeral GetSmoothValueByFastUpdate()
{
int count = this.Count;
RmsedNumeral result = null;
double extraP = 0;//外推的结果
double deltaTail = 0;
if (this.Count <= 1)
{
result = GetFirstOrDefault();
extraP = result.Value;
CurrentData.FittedIonoAndAmbiValue = CurrentData.GetRawIonoAndHalfAmbiValue();
}
else //采用窗口内的数据进行平滑
{
double ionDiffer = 0;
if (IsDeltaIonoCorrect)//电离层改正赋值
{
//var fit = IonoWindow.GetPolyFitValue(CurrentData.Time, OrderOfDeltaIonoPolyFit, IonoFitDataCount);
//if (fit != null)
//{
// CurrentData.FittedIonoAndAmbiValue = fit.Value;
//}
//else
//{
// CurrentData.FittedIonoAndAmbiValue = CurrentData.GetRawIonoAndHalfAmbiValue();
//}
ionDiffer = (CurrentData.FittedIonoAndAmbiValue - PrevData.FittedIonoAndAmbiValue);
}
//所谓的推估表达式，即不采用当前的伪距观测数据， P0 + (L1 - L0) + 2DI
extraP = LastSmoothedRange + (this.CurrentData.PhaseRange - PrevData.PhaseRange) + 2 * ionDiffer;
double sP = extraP;
if (IsWeighted) //加权，表示采用当前的伪距观测数据
{
if (this.LastRemovedItem.Value != null) //当大于指定的窗口，将扣除窗口外的数据（包括电离层延迟）影响。
{
double ionoDiffer = 0;
if (IsDeltaIonoCorrect)
{
ionoDiffer = CurrentData.FittedIonoAndAmbiValue - this.LastRemovedPair.FittedIonoAndAmbiValue;
//var bigFit = BigIonoWindow.GetTimedLsPolyFit(1);
//ionoDiffer = bigFit.GetY( CurrentData.Time) - bigFit.GetY(LastRemovedPair.Time);
}
deltaTail = 1.0 / (this.Count) * (CurrentData.RangeMinusPhase - this.LastRemovedPair.RangeMinusPhase - 2.0 * ionoDiffer);
sP = extraP + deltaTail;
}
else //原始Hatch滤波
{
double weight = GetWeight(this.LastKey, count);
sP = weight * this.CurrentData.PseudoRange + (1 - weight) * extraP;
}
}
double stdDev = this.RawRangeStdDev * 0.1 / Math.Sqrt(count);
result = new RmsedNumeral(sP, stdDev);
//验证算法，2018.06.20, czs，
//var result3 = GetSmoothValueByWholeWindowRecursionAk();
//double ionoDiff;
//double Ak = GetAk(out ionoDiff);
//double akDelta = Ak - PrevAk;
//double differOfAkDelta = akDelta - deltaTail;
////var result2 = this.CurrentRaw.PhaseRange + Ak;
////double differ = result2 - result.Value;
////double differ2 = result2 - result3.Value;
////int oo = 0;
//PrevAk = Ak;
}
this.PrevData = this.CurrentData;
this.LastSmoothedRange = result.Value;
return(result);
}
