Bearing-only tracking with Kalman filters using smoothed measurements
| dc.contributor | Graduate Program in Electrical and Electronic Engineering. | |
| dc.contributor.advisor | Anarım, Emin. | |
| dc.contributor.author | Karakaya, Murat. | |
| dc.date.accessioned | 2023-03-16T10:21:01Z | |
| dc.date.available | 2023-03-16T10:21:01Z | |
| dc.date.issued | 2021. | |
| dc.description.abstract | Kalman filter-based solutions proposed for nonlinear systems are frequently used in bearing-only tracking applications. Due to the physical conditions of these tracking applications, the measurements gathered may contain a high amount of noise. For example, if the measurement sensors are too far from the target being tracked, a small error in the calculated bearing or a small amount of noise exposure will cause the uncertainty in the tracking system to increase significantly. Since the effect of this large amount of noise can only be eliminated to a certain extent by Kalman filter-based solutions, tracking performance may decrease in these applications. In this thesis, various statistical and machine learning-based noise removal methods will be applied to reduce the noise in bearing measurements obtained with sensors. Then, these noise-reduced measurements will be used in Kalman filter-based solutions in bearingonly tracking. The effects of noise reduction methods on tracking performance will be compared with simulations on real vessel trajectories. | |
| dc.format.extent | 30 cm. | |
| dc.format.pages | xx, 89 leaves ; | |
| dc.identifier.other | EE 2021 K37 | |
| dc.identifier.uri | https://digitalarchive.library.bogazici.edu.tr/handle/123456789/13001 | |
| dc.publisher | Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2021. | |
| dc.subject.lcsh | Kalman filtering. | |
| dc.subject.lcsh | Tracking (Engineering) | |
| dc.title | Bearing-only tracking with Kalman filters using smoothed measurements |
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