Class KalmanFilter

Kalman filter. The class implements standard Kalman filter \url{http://en.wikipedia.org/wiki/Kalman_filter}. However, you can modify KalmanFilter::transitionMatrix, KalmanFilter::controlMatrix and KalmanFilter::measurementMatrix to get the extended Kalman filter functionality.

Inheritance
System.Object
DisposableObject
DisposableCvObject
KalmanFilter
Implements
Inherited Members
Namespace: OpenCvSharp
Assembly: OpenCvSharp.dll
Syntax
public class KalmanFilter : DisposableCvObject, ICvPtrHolder

Constructors

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KalmanFilter()

the default constructor

Declaration
public KalmanFilter()
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KalmanFilter(Int32, Int32, Int32, Int32)

the full constructor taking the dimensionality of the state, of the measurement and of the control vector

Declaration
public KalmanFilter(int dynamParams, int measureParams, int controlParams = 0, int type = default(int))
Parameters
Type Name Description
System.Int32 dynamParams
System.Int32 measureParams
System.Int32 controlParams
System.Int32 type

Properties

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ControlMatrix

control matrix (B) (not used if there is no control)

Declaration
public Mat ControlMatrix { get; set; }
Property Value
Type Description
Mat
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ErrorCovPost

posteriori error estimate covariance matrix (P(k)): P(k)=(I-K(k)*H)*P'(k)

Declaration
public Mat ErrorCovPost { get; set; }
Property Value
Type Description
Mat
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ErrorCovPre

priori error estimate covariance matrix (P'(k)): P'(k)=A*P(k-1)At + Q)/

Declaration
public Mat ErrorCovPre { get; set; }
Property Value
Type Description
Mat
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Gain

Kalman gain matrix (K(k)): K(k)=P'(k)Htinv(H*P'(k)*Ht+R)

Declaration
public Mat Gain { get; set; }
Property Value
Type Description
Mat
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MeasurementMatrix

measurement matrix (H)

Declaration
public Mat MeasurementMatrix { get; set; }
Property Value
Type Description
Mat
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MeasurementNoiseCov

measurement noise covariance matrix (R)

Declaration
public Mat MeasurementNoiseCov { get; set; }
Property Value
Type Description
Mat
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ProcessNoiseCov

process noise covariance matrix (Q)

Declaration
public Mat ProcessNoiseCov { get; set; }
Property Value
Type Description
Mat
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StatePost

corrected state (x(k)): x(k)=x'(k)+K(k)(z(k)-Hx'(k))

Declaration
public Mat StatePost { get; set; }
Property Value
Type Description
Mat
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StatePre

predicted state (x'(k)): x(k)=Ax(k-1)+Bu(k)

Declaration
public Mat StatePre { get; set; }
Property Value
Type Description
Mat
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TransitionMatrix

state transition matrix (A)

Declaration
public Mat TransitionMatrix { get; set; }
Property Value
Type Description
Mat

Methods

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Correct(Mat)

updates the predicted state from the measurement

Declaration
public Mat Correct(Mat measurement)
Parameters
Type Name Description
Mat measurement
Returns
Type Description
Mat
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DisposeUnmanaged()

Releases unmanaged resources

Declaration
protected override void DisposeUnmanaged()
Overrides
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Init(Int32, Int32, Int32, Int32)

re-initializes Kalman filter. The previous content is destroyed.

Declaration
public void Init(int dynamParams, int measureParams, int controlParams = 0, int type = default(int))
Parameters
Type Name Description
System.Int32 dynamParams
System.Int32 measureParams
System.Int32 controlParams
System.Int32 type
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Predict(Mat)

computes predicted state

Declaration
public Mat Predict(Mat control = null)
Parameters
Type Name Description
Mat control
Returns
Type Description
Mat

Implements