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http://hdl.handle.net/2123/2242
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| Title: | Radio-Frequency Signal Strength Based Localisation in Unstructured Outdoor Environments |
| Authors: | Kloos, Gerold |
| Keywords: | Localisation, Tracking, Radio-Frequency, Sensor modelling |
| Issue Date: | 31-Aug-2007 |
| Publisher: | Faculty of Engineering and Information Technologies School of Aerospace, Mechanical & Mechatronic Engineering |
| Abstract: | This thesis addresses the issues arising in range-only localisation and tracking using Radio Frequency Received Signal Strength Indicator measurements. One of the key issues in Radio Frequency (RF) based localisation and tracking applications is to obtain an accurate sensor representation. Such a sensor model is one of the prerequisites to achieve high accuracy and precision in the localisation and tracking task. The sensor models used at present for this task are very simplistic, and as a consequence are unable to achieve highly accurate and precise localisation. While such an accurate sensor description is desirable it has not been presented for RF sensors. This thesis addresses the task of obtaining an accurate sensor model for RF sensors. The major drawbacks of the most commonly used model, the nth power model, are demonstrated. A new model to satisfy the necessary requirements for high accuracy localisation is developed. This model is based on theoretical considerations and experimental data. It depicts the real occurring behaviour of RF sensors more closely than the models used so far for RF based range-only localisation. The use of this better sensor representation offers the possibility of achieving more accurate localisation. The expected performance of the alternative sensor model is compared to the commonly used nth power model. Furthermore, the inherent properties of the new sensor model are presented and their ramifications with regards to the goal of achieving highly accurate localisation are discussed. In addition to the sensor model development, the well-known probabilistic filtering techniques Kalman Filter, Particle Filter and Histogram Filter are compared and used to implement 1-dimensional and 2-dimensional range-only trackers. The filtering techniques are evaluated with respect to their suitability for appropriately handling the new multi-modal sensor model and the resulting multi-modal state distributions, and to provide correct and conclusive localisation and tracking results. Results from experiments using real data obtained in outdoor environments with a prototype RF localisation system as well as results obtained from simulations are presented in this thesis to validate the theoretical findings and the newly developed sensor model. |
| Description: | Doctor of Philosophy (PhD) |
| URI: | http://hdl.handle.net/2123/2242 |
| Appears in Collections: | Sydney Digital Theses (Open Access) |
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