KalmanFilter.h File Reference

KalmanRecursion and KalmanFilter (decisions.md [templated-measurements] and [filters-and-recursions]): the Kalman steps over one component as a recursion, a process model and a prediction method acting on a state passed in, and the filter that owns a component and runs that recursion on it, with updates by any measurement reduced to one component by a policy. More...

#include <concepts>
#include <expected>
#include <optional>
#include <type_traits>
#include <utility>
#include <EmrysFilter/Distributions/Component.h>
#include <EmrysFilter/Distributions/Gaussian.h>
#include <EmrysFilter/Distributions/GaussianForm.h>
#include <EmrysFilter/Core/Macros.h>
#include <EmrysFilter/Filters/FilterUpkeep.h>
#include <EmrysFilter/Filters/Recursion.h>
#include <EmrysFilter/Models/FormSteps.h>
#include <EmrysFilter/Models/Measurement.h>
#include <EmrysFilter/Models/ProcessModel.h>
#include <EmrysFilter/Models/Reduction.h>
#include <EmrysFilter/Spaces/Space.h>
#include <EmrysFilter/Models/Transform.h>
#include <EmrysFilter/Core/Print.h>

Go to the source code of this file.

Classes
class	Emrys::KalmanRecursion< Component_, Model_, Method_ >
	The Kalman filter's steps over one component, without the state: a process model and a prediction method, acting on a component passed in (decisions.md [filters-and-recursions]). More...
class	Emrys::KalmanFilter< Component_, Model_, Method_, Recursion_, Upkeep_ >
	A Kalman filter: a Gaussian state and the KalmanRecursion that predicts it through a process model and conditions it on measurements. More...

Concepts
concept	Emrys::KalmanState
	What a KalmanFilter holds and a KalmanRecursion acts on: a Component, such as a Gaussian, or a square-root or information form of the Gaussian (see GaussianForm, decisions.md [gaussian-forms]), whose steps FormSteps.h supplies.

Detailed Description

KalmanRecursion and KalmanFilter (decisions.md [templated-measurements] and [filters-and-recursions]): the Kalman steps over one component as a recursion, a process model and a prediction method acting on a state passed in, and the filter that owns a component and runs that recursion on it, with updates by any measurement reduced to one component by a policy.

The shape every other filter follows, and internal::RecursionFor, which names the recursion a filter over a component runs unless it is given one of the user's own (Recursion.h). Its predictJoint() records a step for the smoother in GaussianHistory.h [smoothing]. Over a square-root or information form of the Gaussian the same recursion runs that form's steps (FormSteps.h, [gaussian-forms]), which InfoFilter.h, SqrtKalmanFilter.h, and SqrtInfoFilter.h spell. Read MixtureFilter.h next.