Bayesian Filtering Library Generated from SVN r
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Particular particle filter: Proposal PDF = Optimal Importance function. More...
#include <optimalimportancefilter.h>
Public Member Functions | |
OptimalImportanceFilter (MCPdf< StateVar > *prior, int resampleperiod=0, double resamplethreshold=0, int resamplescheme=DEFAULT_RS) | |
Constructor. | |
virtual | ~OptimalImportanceFilter () |
Destructor. | |
OptimalImportanceFilter (const OptimalImportanceFilter< StateVar, MeasVar > &filt) | |
Copy constructor. | |
virtual void | Update (SystemModel< StateVar > *const sysmodel, const StateVar &u, MeasurementModel< MeasVar, StateVar > *const measmodel, const MeasVar &z, const StateVar &s) |
Full Update (system with inputs/sensing params) | |
virtual void | Update (SystemModel< StateVar > *const sysmodel, MeasurementModel< MeasVar, StateVar > *const measmodel, const MeasVar &z, const StateVar &s) |
Full Update (system without inputs, with sensing params) | |
virtual void | Update (SystemModel< StateVar > *const sysmodel, MeasurementModel< MeasVar, StateVar > *const measmodel, const MeasVar &z) |
Full Update (system without inputs/sensing params) | |
virtual void | Update (SystemModel< StateVar > *const sysmodel, const StateVar &u, MeasurementModel< MeasVar, StateVar > *const measmodel, const MeasVar &z) |
Full Update (system with inputs, without sensing params) | |
virtual void | Update (SystemModel< StateVar > *const sysmodel, const StateVar &u) |
Only sysupdate. | |
virtual void | Update (SystemModel< StateVar > *const sysmodel) |
System Update (system without inputs) | |
virtual void | Update (MeasurementModel< MeasVar, StateVar > *const measmodel, const MeasVar &z, const StateVar &s) |
Only measupdate. | |
virtual void | Update (MeasurementModel< MeasVar, StateVar > *const measmodel, const MeasVar &z) |
Measurement Update (system without "sensing params") | |
virtual void | ProposalSet (ConditionalPdf< StateVar, StateVar > *const cpdf) |
Set the proposal density. | |
ConditionalPdf< StateVar, StateVar > * | ProposalGet () |
Get a pointer to the proposal density. | |
virtual MCPdf< StateVar > * | PostGet () |
Get Posterior density. | |
virtual void | Reset (Pdf< StateVar > *prior) |
Reset Filter. | |
int | TimeStepGet () const |
Get current time. | |
Protected Attributes | |
ConditionalPdf< StateVar, StateVar > * | _proposal |
Pointer to the Proposal Density. | |
WeightedSample< StateVar > | _sample |
While updating use sample<StateVar> | |
vector< WeightedSample< StateVar > > | _old_samples |
While updating store list of old samples. | |
vector< WeightedSample< StateVar > > | _new_samples |
While updating store list of new samples. | |
vector< Sample< StateVar > > | _new_samples_unweighted |
While resampling. | |
vector< WeightedSample< StateVar > >::iterator | _os_it |
Iterator for old list of samples. | |
vector< WeightedSample< StateVar > >::iterator | _ns_it |
Iterator for new list of samples. | |
int | _resamplePeriod |
Number of timestep between resampling from the Posterior Pdf. | |
double | _resampleThreshold |
Threshold used when dynamic resampling. | |
int | _resampleScheme |
Which resample algorithm (see top of particle.h for #defines) | |
bool | _dynamicResampling |
Dynamic resampling or fixed period resampling? | |
bool | _proposal_depends_on_meas |
Proposal depends on last measurement? | |
bool | _created_post |
created own post | |
Pdf< StateVar > * | _prior |
prior Pdf | |
Pdf< StateVar > * | _post |
Pointer to the Posterior Pdf. | |
int | _timestep |
Represents the current timestep of the filter. | |
Particular particle filter: Proposal PDF = Optimal Importance function.
This is one (simple) particular implementation of a particle filter, in which the proposal density is equal to the pdf
@Article{ doucet98bis, author = {Doucet, Arnaud and Godsill, Simon and Andrieu, Christophe}, title = {On Sequential Monte Carlo Sampling Methods for Bayesian Filtering}, journal = {Statistics and Computing}, year = {2000}, volume = {10}, number = {3}, pages = {197--208}, }
for a more thorough discussion about all these issues and the possible suboptimal alternatives in case one is not able to sample from the optimal importance function.
Definition at line 67 of file optimalimportancefilter.h.
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protectedvirtual |
Construct Optimal importance density from a sys and meas. model.
sysmodel | system model to use |
measmodel | measurement model to use for proposal construction |
Resample if necessary.
OptimalImportanceFilter | ( | MCPdf< StateVar > * | prior, |
int | resampleperiod = 0, | ||
double | resamplethreshold = 0, | ||
int | resamplescheme = DEFAULT_RS ) |
Constructor.
prior | pointer to the Monte Carlo Pdf prior density |
resampleperiod | fixed resampling period (if desired) |
resamplethreshold | threshold used when dynamic resampling |
resamplescheme | resampling scheme, see header file for different defines and their meaning |
Get Posterior density.
Get the current Posterior density
Reimplemented from Filter< StateVar, MeasVar >.
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inherited |
Get a pointer to the proposal density.
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virtualinherited |
Set the proposal density.
cpdf | the new proposal density. The order of the conditional arguments is fixed and should be: x (state), u (input), z (measurement), s (sensor param). Off course all of them are optional |
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protectedvirtualinherited |
Proposal step.
Implementation of proposal step
sysmodel | pointer to the used system model |
u | input param for proposal density |
measmodel | pointer to the used measurementmodel |
z | measurement param for proposal density |
s | sensor param for proposal density |
Reimplemented in EKParticleFilter.
Actual Resampling happens here;.
Reimplemented in EKParticleFilter.
Resample if wanted.
Get current time.
Get the current time of the filter
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virtual |
Measurement Update (system without "sensing params")
measmodel | pointer to the measurement model to use for update |
z | measurement |
Reimplemented from Filter< StateVar, MeasVar >.
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virtual |
Only measupdate.
Reimplemented from Filter< StateVar, MeasVar >.
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virtual |
System Update (system without inputs)
sysmodel | pointer to the system model to use for update |
Reimplemented from Filter< StateVar, MeasVar >.
Only sysupdate.
Reimplemented from Filter< StateVar, MeasVar >.
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virtual |
Full Update (system with inputs, without sensing params)
sysmodel | pointer to the system model to use for update |
u | input to the system |
measmodel | pointer to the measurement model to use for update |
z | measurement |
Reimplemented from Filter< StateVar, MeasVar >.
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virtual |
Full Update (system with inputs/sensing params)
sysmodel | pointer to the system model to use for update |
u | input to the system |
measmodel | pointer to the measurement model to use for update |
z | measurement |
s | "sensing parameter" |
Reimplemented from Filter< StateVar, MeasVar >.
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virtual |
Full Update (system without inputs/sensing params)
sysmodel | pointer to the system model to use for update |
measmodel | pointer to the measurement model to use for update |
z | measurement |
Reimplemented from Filter< StateVar, MeasVar >.
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virtual |
Full Update (system without inputs, with sensing params)
sysmodel | pointer to the system model to use for update |
measmodel | pointer to the measurement model to use for update |
z | measurement |
s | "sensing parameter" |
Reimplemented from Filter< StateVar, MeasVar >.
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protectedvirtualinherited |
Actual implementation of Update, varies along filters.
sysmodel | pointer to the used system model |
u | input param for proposal density |
measmodel | pointer to the used measurementmodel |
z | measurement param for proposal density |
s | sensor param for proposal density |
Implements Filter< StateVar, MeasVar >.
Reimplemented in ASIRFilter< StateVar, MeasVar >, and BootstrapFilter< StateVar, MeasVar >.
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protectedvirtualinherited |
Update Weights.
sysmodel | pointer to the used system model |
u | input param for proposal density |
measmodel | pointer to the used measurementmodel |
z | measurement param for proposal density |
s | sensor param for proposal density |
created own post
Definition at line 208 of file particlefilter.h.
Dynamic resampling or fixed period resampling?
Definition at line 202 of file particlefilter.h.
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protectedinherited |
While updating store list of new samples.
Definition at line 181 of file particlefilter.h.
While resampling.
Definition at line 183 of file particlefilter.h.
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protectedinherited |
Iterator for new list of samples.
Definition at line 187 of file particlefilter.h.
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protectedinherited |
While updating store list of old samples.
Definition at line 179 of file particlefilter.h.
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protectedinherited |
Iterator for old list of samples.
Definition at line 185 of file particlefilter.h.
Pointer to the Posterior Pdf.
The Posterior Pdf represents the subjective belief of the person applying the filter AFTER processing inputs and measurements. A filter does not maintain the beliefs at all timesteps t, since this leads to non-constant (or ever growing if you prefer) memory requirements. However, it is possible, to copy the Posterior density at all timesteps in your application by means of the PostGet() member function
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protectedinherited |
Pointer to the Proposal Density.
Every particle filter (or more correct: every Sequential Importance Sampling method) uses a proposal density to do the forward sampling step
Definition at line 174 of file particlefilter.h.
Proposal depends on last measurement?
Definition at line 205 of file particlefilter.h.
Number of timestep between resampling from the Posterior Pdf.
By choosing this period, one can avoid numerical instability (aka Degeneration of the particle filter
Definition at line 193 of file particlefilter.h.
Which resample algorithm (see top of particle.h for defines)
Definition at line 199 of file particlefilter.h.
Threshold used when dynamic resampling.
Definition at line 196 of file particlefilter.h.
While updating use sample<StateVar>
Definition at line 177 of file particlefilter.h.