#include <Measurements.hpp>

Public Member Functions
virtual int16	calculateMeasurements (floating_point time, const std::array< floating_point, N > &tar_state, const std::array< floating_point, O > &obs_state, floating_point expected_measurement[M])
	Function to calculate a measurement from current state of system.
virtual int16	calculateMeasurementsMatrix (floating_point time, const std::array< floating_point, N > &tar_state, const std::array< floating_point, O > &obs_state, floating_point measurement_Jacobian[M *N])
	Function to calculate the measurement function Jacobian from current state of system.

Detailed Description

template<uint32 N, uint32 M, uint32 O>
class warpos::Measurements< N, M, O >

The measurements class defines a generic, templated base class which may be used generically as a measurement update in the EKF measurement update class. The values N, M, O, and R should be assigned and are defined as follows: N - The number of states in the target state vector. i.e. 3 for [x, y, z] M - The number of measurements produced by the function. i.e. 2 for [range, rangerate]. Also the number of states in the R vector. O - The number of observer states. May be unused but could be i.e. another [x, y, z] for range

This class should be inherited from for each sensor used on a system

Author: James Tabony james.nosp@m..tab.nosp@m.ony@a.nosp@m.ttx..nosp@m.tech

Member Function Documentation

◆ calculateMeasurements()

template<uint32 N, uint32 M, uint32 O>

virtual int16 warpos::Measurements< N, M, O >::calculateMeasurements	(	floating_point	time,
		const std::array< floating_point, N > &	tar_state,
		const std::array< floating_point, O > &	obs_state,
		floating_point	expected_measurement[M] )

inlinevirtual

Function to calculate a measurement from current state of system.

Parameters

[in]	time	The reference time
[in]	tar_state	The target reference state
[in]	obs_state	The observer reference state
[out]	expected_measurement	Implicit return of measurements based on time and state

Returns: Error return code, zero means no error

◆ calculateMeasurementsMatrix()