EECI08: State Estimation and Sensor Fusion

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This lecture provides a review of key results in state estimation and sensor fusion that will be built upon in future lectures. We briefly summarize Kalman filtering and discuss several variants that are of use in a computationally-rich, networked environment: information filters, moving horizon estimation and particle filters.

Outline Kalman Filtering Sensor Fusion Extensions Information Filters Moving Horizon Estimation Particle Filters

Lecture Materials Lecture slides: State Estimation and Sensor Fusion Lecture notes: NCS06, Chapter 4 - State Estimation and Sensor Fusion Additional Information