Trackers

class stonesoup.tracker.base.Tracker[source]

Bases: Base

Tracker base class

class stonesoup.tracker.simple.SingleTargetTracker(initiator: Initiator, deleter: Deleter, detector: DetectionReader, data_associator: DataAssociator, updater: Updater)[source]

Bases: _TrackerMixInNext, Tracker

A simple single target tracker.

Track a single object using Stone Soup components. The tracker works by first calling the data_associator with the active track, and then either updating the track state with the result of the updater if a detection is associated, or with the prediction if no detection is associated to the track. The track is then checked for deletion by the deleter, and if deleted the initiator is called to generate a new track. Similarly if no track is present (i.e. tracker is initialised or deleted in previous iteration), only the initiator is called.

Parameters:

initiator (Initiator) – Initiator used to initialise the track.
deleter (Deleter) – Deleter used to delete tracks.
detector (DetectionReader) – Detector used to generate detection objects.
data_associator (DataAssociator) – Association algorithm to pair predictions to detections
updater (Updater) – Updater used to update the track object to the new state.

track

Current track being maintained. Also accessible as the sole item in tracks

Type:: Track

initiator: Initiator: Initiator used to initialise the track.

deleter: Deleter: Deleter used to delete tracks.

detector: DetectionReader: Detector used to generate detection objects.

data_associator: DataAssociator: Association algorithm to pair predictions to detections

updater: Updater: Updater used to update the track object to the new state.

update_tracker(time: datetime, detections: set[Detection]) → tuple[datetime, set[Track]]

Use time and detections to create tracks.

This is an alternative to iterating over the tracker, instead the tracker can be progressed by multiple calls to this method.

Parameters:

time (datetime.datetime) – Datetime of current time step
detections (set of Detection) – Detections existing in the time step to be tracked

Returns:

datetime.datetime – Datetime of current time step
set of Track – Tracks existing in the time step

class stonesoup.tracker.simple.SingleTargetMixtureTracker(initiator: Initiator, deleter: Deleter, detector: DetectionReader, data_associator: DataAssociator, updater: Updater)[source]

Bases: _TrackerMixInNext, Tracker

A simple single target tracking that receives associations from a (Gaussian) Mixture associator.

Track single objects using Stone Soup components. The tracker works by first calling the data_associator with the active track, and then either updating the track state with the result of the data_associator that reduces the (Gaussian) Mixture of all possible track-detection associations, or with the prediction if no detection is associated to the track. The track is then checked for deletion by the deleter, and remaining unassociated detections are passed to the initiator to generate new track.

Parameters:

initiator (Initiator) – Initiator used to initialise the track.
deleter (Deleter) – Deleter used to delete tracks.
detector (DetectionReader) – Detector used to generate detection objects.
data_associator (DataAssociator) – Association algorithm to pair predictions to detections
updater (Updater) – Updater used to update the track object to the new state.

initiator: Initiator: Initiator used to initialise the track.

deleter: Deleter: Deleter used to delete tracks.

detector: DetectionReader: Detector used to generate detection objects.

data_associator: DataAssociator: Association algorithm to pair predictions to detections

updater: Updater: Updater used to update the track object to the new state.

update_tracker(time: datetime, detections: set[Detection]) → tuple[datetime, set[Track]]

Use time and detections to create tracks.

This is an alternative to iterating over the tracker, instead the tracker can be progressed by multiple calls to this method.

Parameters:

time (datetime.datetime) – Datetime of current time step
detections (set of Detection) – Detections existing in the time step to be tracked

Returns:

datetime.datetime – Datetime of current time step
set of Track – Tracks existing in the time step

class stonesoup.tracker.simple.MultiTargetTracker(initiator: Initiator, deleter: Deleter, detector: DetectionReader, data_associator: DataAssociator, updater: Updater)[source]

Bases: _TrackerMixInNext, Tracker

A simple multi target tracker.

Track multiple objects using Stone Soup components. The tracker works by first calling the data_associator with the active tracks, and then either updating the track state with the result of the updater if a detection is associated, or with the prediction if no detection is associated to the track. Tracks are then checked for deletion by the deleter, and remaining unassociated detections are passed to the initiator to generate new tracks.

Parameters:

initiator (Initiator) – Initiator used to initialise the track.
deleter (Deleter) – Deleter used to delete tracks.
detector (DetectionReader) – Detector used to generate detection objects.
data_associator (DataAssociator) – Association algorithm to pair predictions to detections
updater (Updater) – Updater used to update the track object to the new state.

initiator: Initiator: Initiator used to initialise the track.

deleter: Deleter: Deleter used to delete tracks.

detector: DetectionReader: Detector used to generate detection objects.

data_associator: DataAssociator: Association algorithm to pair predictions to detections

updater: Updater: Updater used to update the track object to the new state.

update_tracker(time: datetime, detections: set[Detection]) → tuple[datetime, set[Track]]

Use time and detections to create tracks.

This is an alternative to iterating over the tracker, instead the tracker can be progressed by multiple calls to this method.

Parameters:

time (datetime.datetime) – Datetime of current time step
detections (set of Detection) – Detections existing in the time step to be tracked

Returns:

datetime.datetime – Datetime of current time step
set of Track – Tracks existing in the time step

class stonesoup.tracker.simple.MultiTargetMixtureTracker(initiator: Initiator, deleter: Deleter, detector: DetectionReader, data_associator: DataAssociator, updater: Updater)[source]

Bases: _TrackerMixInNext, Tracker

A simple multi target tracker that receives associations from a (Gaussian) Mixture associator.

Track multiple objects using Stone Soup components. The tracker works by first calling the data_associator with the active tracks, and then either updating the track state with the result of the data_associator that reduces the (Gaussian) Mixture of all possible track-detection associations, or with the prediction if no detection is associated to the track. Tracks are then checked for deletion by the deleter, and remaining unassociated detections are passed to the initiator to generate new tracks.

Parameters:

initiator (Initiator) – Initiator used to initialise the track.
deleter (Deleter) – Deleter used to delete tracks.
detector (DetectionReader) – Detector used to generate detection objects.
data_associator (DataAssociator) – Association algorithm to pair predictions to detections
updater (Updater) – Updater used to update the track object to the new state.

initiator: Initiator: Initiator used to initialise the track.

deleter: Deleter: Deleter used to delete tracks.

detector: DetectionReader: Detector used to generate detection objects.

data_associator: DataAssociator: Association algorithm to pair predictions to detections

updater: Updater: Updater used to update the track object to the new state.

update_tracker(time: datetime, detections: set[Detection]) → tuple[datetime, set[Track]]

Use time and detections to create tracks.

This is an alternative to iterating over the tracker, instead the tracker can be progressed by multiple calls to this method.

Parameters:

time (datetime.datetime) – Datetime of current time step
detections (set of Detection) – Detections existing in the time step to be tracked

Returns:

datetime.datetime – Datetime of current time step
set of Track – Tracks existing in the time step

Point Process

class stonesoup.tracker.pointprocess.PointProcessMultiTargetTracker(detector: DetectionReader, updater: Updater, hypothesiser: GaussianMixtureHypothesiser, reducer: GaussianMixtureReducer, extraction_threshold: Probability = 0.9, birth_component: TaggedWeightedGaussianState = None)[source]

Bases: _TrackerMixInNext, Tracker

Base class for Gaussian Mixture (GM) style implementations of point process derived filters

Parameters:

detector (DetectionReader) – Detector used to generate detection objects.
updater (Updater) – Updater used to update the objects to their new state.
hypothesiser (GaussianMixtureHypothesiser) – Association algorithm to pair predictions to detections
reducer (GaussianMixtureReducer) – Reducer used to reduce the number of components in the mixture.
extraction_threshold (Probability, optional) – Threshold to extract components from the mixture.
birth_component (TaggedWeightedGaussianState, optional) – The birth component. The weight should be equal to the mean of the expected number of births per timestep (Poission distributed). The tag should be TaggedWeightedGaussianState.BIRTH

detector: DetectionReader: Detector used to generate detection objects.

updater: Updater: Updater used to update the objects to their new state.

hypothesiser: GaussianMixtureHypothesiser: Association algorithm to pair predictions to detections

reducer: GaussianMixtureReducer: Reducer used to reduce the number of components in the mixture.

extraction_threshold: Probability: Threshold to extract components from the mixture.

birth_component: TaggedWeightedGaussianState: The birth component. The weight should be equal to the mean of the expected number of births per timestep (Poission distributed). The tag should be TaggedWeightedGaussianState.BIRTH

update_tracks()[source]

Updates the tracks (Track) associated with the filter.

Parameters:: self (GaussianMixtureMultiTargetTracker) – Current GM Multi Target Tracker at time \(k\)

Note

Each track shares a unique tag with its associated component

end_tracks()[source]

Ends the tracks (Track) that do not have an associated component within the filter.

Parameters:: self (GaussianMixtureMultiTargetTracker) – Current GM Multi Target Tracker at time \(k\)

property extracted_target_states: Extract all target states from the Gaussian Mixture that are above an extraction threshold.

property estimated_number_of_targets: The number of hypothesised targets.

update_tracker(time: datetime, detections: set[Detection]) → tuple[datetime, set[Track]]

Use time and detections to create tracks.

This is an alternative to iterating over the tracker, instead the tracker can be progressed by multiple calls to this method.

Parameters:

time (datetime.datetime) – Datetime of current time step
detections (set of Detection) – Detections existing in the time step to be tracked

Returns:

datetime.datetime – Datetime of current time step
set of Track – Tracks existing in the time step