Both the trackingUKF and unscentedKalmanFilter functions in MATLAB implement the Unscented Kalman Filter (UKF), but they are designed for different purposes and application areas. Here is a summary of their differences:
trackingUKF Function:
- Purpose: Part of the Sensor Fusion and Tracking Toolbox, this function is specifically built for tracking applications, such as object tracking where the state may include position, velocity, and other kinematic properties.
- Features: Integrated with MATLAB’s tracking framework, it offers multi-object tracking, track management, sensor fusion, and supports various motion and measurement models. Additional features include track initialization, maintenance, and deletion.
- Use Case: Well-suited for tracking applications, especially those involving multiple objects or complex sensor fusion scenarios. More details are available with:
web(fullfile(docroot, 'fusion/ref/trackingukf.html'))
unscentedKalmanFilter Function:
- Purpose: This is a general-purpose UKF implementation available in MATLAB without extra toolboxes. It is suitable for a broad range of applications beyond tracking, such as state estimation in control systems or nonlinear dynamic systems.
- Features: Allows custom definition of state transition and measurement functions, and provides flexibility for specifying process and measurement noise. It is intended for straightforward UKF implementation without tracking-specific features.
- Use Case: A good choice for general state estimation or control problems where tracking-specific features are not needed. Further information can be found with:
web(fullfile(docroot, 'ident/ref/unscentedkalmanfilter.html'))
The trackingUKF function requires the Sensor Fusion and Tracking Toolbox, while unscentedKalmanFilter is available within the Control System Toolbox. The decision between the two depends on the specific requirements of the application and the desired level of integration with MATLAB’s tracking framework. If both options are available, prototyping with each can help determine which is the best fit for the intended use.
