Examples
Here are a selection of examples of Stone Soup features.
Classification Using Hidden Markov Model
Comparing Efficient Hypothesis Management (EHM) with probability associators
Use of Custom Readers that support Pandas DataFrames
Disjoint Tracking and Classification
Performance comparison between Kalman and Particle Filters
Kalman filter with Out-of-Sequence measurements
Multi-Frame Assignment example
Multi-Target Tracking in 3D Using Platform Simulation
Multi-Sensor Moving Platform Simulation Example
Comparing Multiple Trackers On Manoeuvring Targets
Generic One-to-One Association Examples
Particle filtering with Out-of-sequence Measurements
Reinforcement Learning Sensor Manager
Creating Smooth Transitions Between Coordinates
Multi-Sensor Fusion: Covariance Intersection Using Tracks as Measurements
Bearings-only tracking example
Handling OOSM using inverse time dynamics
Dealing with Out-Of-Sequence Measurements with a fixed lag storage
RangeRangeRateBinning measurement model example
Comparing different filters in the context of track fusion