Tutorials
Here are some tutorials on using Stone Soup that also introduce some topics of state estimation and tracking.
1 - An introduction to Stone Soup: using the Kalman filter
2 - Non-linear models: extended Kalman filter
3 - Non-linear models: unscented Kalman filter
4 - Sampling methods: particle filter
5 - Data association - clutter tutorial
6 - Data association - multi-target tracking tutorial
7 - Probabilistic data association tutorial
8 - Joint probabilistic data association tutorial
10 - Tracking in simulation: bringing all components together
Data association
Here are some tutorials which cover additional data association techniques.
Filters
Here are some tutorials which cover additional filtering techniques.
Kernel methods: the adaptive kernel Kalman filter
Accumulated States Densities - Out-of-Sequence measurements
Sampling
Here are some tutorials which cover sampling techniques.
Particle Filter Resamplers: Tutorial
Sensor Management
Here are some tutorials that introduce sensor management using Stone Soup classes.
2 - Multiple Sensor Management
3 - Optimised Sensor Management