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Institutional Repository [SANDBOX]
Technical University of Crete
Technical University of Crete
EN
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EL
| URI | http://purl.tuc.gr/dl/dias/818E7D7F-57C8-4672-8B90-CECFC2576B8A | - |
| Identifier | https://doi.org/10.26233/heallink.tuc.20591 | - |
| Language | en | - |
| Extent | 74 pages | en |
| Title | Smart sensors of RF and backscatter signals with localization | en |
| Creator | Alimpertis Emmanouil | en |
| Creator | Αλιμπερτης Εμμανουηλ | el |
| Contributor [Thesis Supervisor] | Bletsas Aggelos | en |
| Contributor [Thesis Supervisor] | Μπλετσας Αγγελος | el |
| Contributor [Committee Member] | Karystinos Georgios | en |
| Contributor [Committee Member] | Καρυστινος Γεωργιος | el |
| Contributor [Committee Member] | Lagoudakis Michael | en |
| Contributor [Committee Member] | Λαγουδακης Μιχαηλ | el |
| Publisher | Πολυτεχνείο Κρήτης | el |
| Publisher | Technical University of Crete | en |
| Academic Unit | Technical University of Crete::School of Electronic and Computer Engineering | en |
| Academic Unit | Πολυτεχνείο Κρήτης::Σχολή Ηλεκτρονικών Μηχανικών και Μηχανικών Υπολογιστών | el |
| Description | Master Thesis | el |
| Content Summary | Information may be more valuable when the location of its source is known. This thesis develops localization algorithms based on received signal strength (RSS) measurements for unknown radio frequency (RF) sources and bistatic scatter radio tags (sensors). This thesis demonstrates RF source location es- timation utilizing RSS measurements by a community of smartphone users, within 800m (or more) from the source. The location estimation algorithm incorporates careful modeling of the time-varying source transmission power, source antenna directionality (even with a single 4-parameter model) and different path loss exponents among the various source-user links. More im- portantly, a vast number of measurements is collected and exploited through an automated community of smartphones. Location estimation error on the order of 50m is achieved, even when users are within 800m or more from the RF source. Furthermore, multiple input single output RSS localization for bistatic scatter radio is also considered. The RF scatter radio tag is illuminated by multiple low-cost carrier emitters, operating consecutively. Experimental validation of the proposed algorithm reports localization error on the order of 3m for tag and emitters placed at an area of 70m x 70m. Both estimation algorithms on real-world data exploit non-parametric estimation based on particle filtering. | en |
| Type of Item | Μεταπτυχιακή Διατριβή | el |
| Type of Item | Master Thesis | en |
| License | http://creativecommons.org/licenses/by-nc-sa/4.0/ | en |
| Date of Item | 2014-10-14 | - |
| Date of Publication | 2014 | - |
| Subject | Sensor localizaiton with multiple emitters | en |
| Subject | RF-tag localization | en |
| Subject | Particle filtering | en |
| Subject | Non-parametric estimation | en |
| Subject | Community RF sensing | en |
| Subject | RF sources | en |
| Subject | Localization | en |
| Bibliographic Citation | Emmanouil Alimpertis, "Smart sensors of RF and backscatter signals with localization", Master Thesis, School of Electronic and Computer Engineering, Technical University of Crete, Chania, Greece, 2014 | en |
| Bibliographic Citation | Εμμανουήλ Αλιμπέρτης, "Smart sensors of RF and backscatter signals with localization", Μεταπτυχιακή Διατριβή, Σχολή Ηλεκτρονικών Μηχανικών και Μηχανικών Υπολογιστών, Πολυτεχνείο Κρήτης, Χανιά, Ελλάς, 2014 | el |
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