measurementModels

Executive Summary

This class provides an container for all the measurement models and components to a kalman filter. This class is a necessary component to any Kalman Filter implementation

Virtual and Private method descriptors

The following table lists all the class methods and their function

Interface methods which remain private

Method Name	Method Function	Protected or Private	Virtual or not
model	compute measurement model give a state	public	necessary
computeMeasurementMatrix	compute measurement matrix give a state	public	necessary

Module assumptions and limitations

None

User Guide

This section lists all the setters and getters that are defined by the interface

Interface methods which remain private

Method Name	Method Function	Necessity
get/setMeasurementName	set the name of the measurement to distinguish it from others	necessary
get/setTimeTag	set the measurement time tag	necessary
get/setValidity	set the measurement validity	necessary
get/setObservation	set the measurement observation value	necessary
get/setMeasurementNoise	set the measurement noise matrix	necessary
get/setPreFitResiduals	set the measurement pre fit residuals	necessary
get/setPostFitResiduals	set the measurement pre fit residuals	necessary

Static methods for common measurement models

Method Name	Method Function
positionStates	measurement of position state
normalizedPositionStates	measurement of heading direction
mrpStates	measurement of position state with a shadow set check
velocityStates	measurement of velocity states

class MeasurementModel

Container class for measurement data and models.

Public Functions

Eigen::MatrixXd model(const FilterStateVector &state) const

Function to represent measurement model which inputs a stateModel and outputs a matrix

Parameters:

FilterStateVector –

Returns:

Eigen::MatrixXd

void setMeasurementModel(const std::function<const Eigen::MatrixXd(const FilterStateVector&)> &modelCalculator)

Set function to represent measurement model which inputs a stateModel and outputs a matrix

Parameters:

std::function<const – Eigen::MatrixXd(const FilterStateVector&)>

Eigen::MatrixXd computeMeasurementMatrix(const FilterStateVector &state) const

Function to represent measurement matrix which inputs a stateModel and outputs a matrix (partial of measurement

Parameters:

FilterStateVector –

Returns:

Eigen::MatrixXd

void setMeasurementMatrix(const std::function<const Eigen::MatrixXd(const FilterStateVector&)> &hMatrixCalculator)

Set function to represent measurement matrix which inputs a stateModel and outputs a matrix (partial of measurement model with respect to state)

Parameters:

std::function<const – Eigen::MatrixXd(const FilterStateVector&)>

Eigen::VectorXd subMeasurements(const Eigen::VectorXd &measurementObserved, const Eigen::VectorXd &measurementPredicted) const

Subtract measurements. By default this is a linear subtraction, but could be subMrp or other functions depending on the measurement type

Parameters:

• Eigen::VectorXd – measurementObserved

• Eigen::VectorXd – measurementPredicted

Returns:

Eigen::VectorXd

void setMeasurementSubtraction(const std::function<const Eigen::VectorXd(const Eigen::VectorXd&, const Eigen::VectorXd&)> &add)

Set function to add measurements. By default this add function is an R^n subtraction, but could be subMrp or other functions depending on the measurement type

Parameters:

subFunction – std::function<const Eigen::VectorXd(const Eigen::VectorXd&, const Eigen::VectorXd&)>

size_t size() const

Return the size of the observation

Returns:

size_t

std::string getMeasurementName() const

Get measurement name

Returns:

std::string

void setMeasurementName(std::string_view measurementName)

Set measurement name

Parameters:

std::string –

double getTimeTag() const

Get measurement time tag

Returns:

double

void setTimeTag(double measurementTimeTag)

Set measurement time tag

Parameters:

double –

bool getValidity() const

Get measurement validity

Returns:

Eigen::VectorXd

void setValidity(bool measurementValidity)

Set measurement validity

Parameters:

bool –

Eigen::VectorXd getObservation() const

Get measurement observation

Returns:

Eigen::VectorXd

void setObservation(const Eigen::VectorXd &measurementObserved)

Set measurement observation

Parameters:

Eigen::VectorXd –

Eigen::MatrixXd getMeasurementNoise() const

Get measurement noise

Returns:

Eigen::MatrixXd

void setMeasurementNoise(const Eigen::MatrixXd &measurementNoise)

Set measurement noise

Parameters:

Eigen::MatrixXd –

Eigen::VectorXd getPreFitResiduals() const

Get pre fit residuals of observation

Returns:

Eigen::VectorXd

void setPreFitResiduals(const Eigen::VectorXd &measurementPreFit)

Set pre fit residuals of observation

Parameters:

Eigen::VectorXd –

Eigen::VectorXd getPostFitResiduals() const

Get post fit residuals of observation

Returns:

Eigen::VectorXd

void setPostFitResiduals(const Eigen::VectorXd &measurementPostFit)

Set post fit residuals of observation

Parameters:

Eigen::VectorXd –

Public Static Functions

static Eigen::VectorXd positionStates(const FilterStateVector &state)

Measurement model that returns the position component of the state

Parameters:

FilterStateVector – state

Returns:

Eigen::VectorXd

static Eigen::VectorXd normalizedPositionStates(const FilterStateVector &state)

Measurement model that returns the unit vector of the position state

Parameters:

FilterStateVector – state

Returns:

Eigen::VectorXd

static Eigen::VectorXd mrpStates(const FilterStateVector &state)

Measurement model that returns the position component of the state, and performs a MRP shadow set check

Parameters:

FilterStateVector – state

Returns:

Eigen::VectorXd

static Eigen::VectorXd velocityStates(const FilterStateVector &state)

Measurement model that returns the velocity component of the state

Parameters:

state –

Returns:

Eigen::VectorXd

static Eigen::VectorXd velocityStatesWithBias(const FilterStateVector &state)

Measurement model that returns the velocity component of the state with Bias

Parameters:

FilterStateVector – state

Returns:

Eigen::VectorXd