Sensor Fusion (TSRT14)
Preliminary Lecture and Exercise Session Plan
Lectures
Updated slides will be available before each lecture.
The indicated chapters indicates which chapters in the textbook are covered during the lecture.
| Nr | Content | Chapter | Slides |
|---|---|---|---|
| 1 | Course overview. Estimation theory for linear models. | Ch 1, 2 | 1up, 4up |
| 2 | Estimation theory for nonlinear models. | Ch 3 | 1up, 4up |
| 3 | Cramér-Rao lower bound (CRLB). Models for sensor network applications. | Ch 4 | 1up, 4up |
| 4 | Detection theory. Filter theory. | Ch 5, 6 | 1up, 4up |
| 5 | Modeling and motion models. | Ch 12–14 | 1up, 4up |
| 6 | Kalman filter. Kalman filter approximations for nonlinear models (EKF, UKF). | Ch 7, 8 | 1up, 4up |
| 7 | The point-mass filter and the particle filter. | Ch 9 | 1up, 4up |
| 8 | The particle filter theory. The marginalized particle filter. | Ch 9 | 1up, 4up |
| 9 | Simultaneous localization and mapping (SLAM). | Ch 11 | 1up, 4up |
| 10 | Case studies from industry. Sensors and sensor-near signal processing. Filter and model validation. | Ch 14, 15 | 1up, 4up |
Exercise Sessions
The exercises refer to exercises in the recommended exercise book.
| Nr | Content | Exercises |
|---|---|---|
| 1 | Estimation | 2.1, 2.4, 3.1, 3.2, 3.6b, 2.3, 2.5 |
| 2 | Sensor networks and detection | 4.10, 4.2, 4.3, 5.3, 16.1 |
| 3 | Computer-based estimation and detection | 2.10, 3.10, 3.7, 4.7, 4.8, 4.9, 5.4 |
| 4 | Filter theory and models | 6.1, 6.2, 12.1, 12.2, 13.2, (12.3), (13.1) |
| 5 | Kalman filters and Kalman filter approximations | 7.1, 7.2, 7.3, 8.1, 8.2, 8.4 |
| 6 | Computer-based filtering | 7.10, 8.6, 9.5, (16.3) |
| 7 | Computer-based SLAM | 11.1, 11.3 |
| 8 | Particle filtering and sensors | 9.1, 9.2, 9.3, 14.2 |
Exercise sessions 3, 7, and 7 are more practical in their nature than the five other exercise sessions. Most of the exercises covered during these sessions involve using Matlab and SigSys to experiment with the methods described in the course. Hence, to get the most out of these sessions, please bring a laptop with (Matlab and SigSys installed) to these sessions, or pair up with someone that does.