Public Member Functions
	CorrectionInProgress (StateType &state, MeasurementType &meas, types::SquareMatrix< n > const &P_, types::Matrix< n, m > const &PHt_, types::SquareMatrix< m > const &S)

bool	finishCorrection (bool cancelIfNotFinite=true)
	That's as far as we go here before you choose to continue. More...

Public Attributes
types::SquareMatrix< n >	P
	State error covariance.

types::Matrix< n, m >	PHt
	The kalman gain stuff to not invert (called P12 in TAG)

Eigen::LDLT< types::SquareMatrix< m > >	denom
	Decomposition of S. More...

types::Vector< m >	deltaz
	Measurement residual/delta z/innovation.

types::Vector< n >	stateCorrection
	Corresponding state change to apply.

bool	stateCorrectionFinite
	Is the state correction free of NaNs and +- infs?

Static Public Attributes
static const types::DimensionType	m
	Dimension of measurement. More...

static const types::DimensionType	n
	Dimension of state. More...

Member Function Documentation

§ finishCorrection()

template<typename StateType, typename MeasurementType>

bool osvr::kalman::CorrectionInProgress< StateType, MeasurementType >::finishCorrection ( bool cancelIfNotFinite = true )

inline

That's as far as we go here before you choose to continue.

Finish computing the rest and correct the state.

Parameters

cancelIfNotFinite If the new error covariance is detected to contain non-finite values, should we cancel the correction and not apply it?

Returns: true if correction completed

Member Data Documentation

§ denom

template<typename StateType, typename MeasurementType>

Eigen::LDLT<types::SquareMatrix<m> > osvr::kalman::CorrectionInProgress< StateType, MeasurementType >::denom

Decomposition of S.

Not going to directly compute Kalman gain K = PHt (S^-1) Instead, decomposed S to solve things of the form (S^-1)x repeatedly later, by using the substitution Kx = PHt denom.solve(x)