3. Unscented Kalman Filter User’s Guide
같은점 : Like the Kalman Filter, the Unscented Kalman Filter is an unsupervised algorithm for tracking a single target in a continuous state space.
다른점 : The difference is that while the Kalman Filter restricts dynamics to affine functions, the Unscented Kalman Filter is designed to operate under arbitrary dynamics.
장점 The advantages of the Unscented Kalman Filter implemented here are:
- Ability to handle non-affine state transition and observation functions
- Ability to handle not-quite-Gaussian noise models
- Same computational complexity as the standard Kalman Filter
단점 The disadvantages are:
- No method for learning parameters
- Lack of theoretical guarantees on performance
- Inability to handle extremely non-Gaussian noise