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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Rigatos, G.G. |
| Copyright Year | 2010 |
| Abstract | The paper provides technical analysis and implementation cost assessment of Sigma-Point Kalman Filtering and Particle Filtering in autonomous navigation systems. As a case study, the sensor fusion-based navigation of an unmanned aerial vehicle (UAV) is examined. The UAV tracks a desirable flight trajectory by fusing measurements coming from its Inertial Measurement Unit (IMU) and measurements which are received from a satellite or ground-based positioning system (e.g. GPS or radar). The estimation of the UAV's state vector is performed with the use of (i) Sigma-Point Kalman Filtering (SPKF), (ii) Particle Filtering (PF). Trajectory tracking is succeeded by a nonlinear controller which is derived according to flatness-based control theory and which uses the UAV's state vector estimated through filtering. The performance of the remote sensing navigation system which is based on the aforementioned state estimation methods is evaluated through simulation tests. |
| Starting Page | 1 |
| Ending Page | 5 |
| File Size | 293255 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781424425181 |
| ISSN | 15502252 |
| DOI | 10.1109/VETECS.2010.5493639 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-05-16 |
| Publisher Place | Taiwan |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Filtering Costs Kalman filters Unmanned aerial vehicles State estimation Satellite navigation systems Radar tracking Trajectory Position measurement Measurement units |
| Content Type | Text |
| Resource Type | Article |
| Subject | Applied Mathematics Electrical and Electronic Engineering Computer Science Applications |
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