Work described in this thesis is concerned with localisation techniques, for determining the position, of wireless sensors whilst these are immersed in confined industrial processes, such as those occurring in the chemical, pharmaceutical and food processing industries. Two different approaches to localisation were investigated. The first approach employed an existing hardware system that used ultra wide band (UWB) signals whist the second approach used a network localisation method based on information from narrow-band received signals. A prototype UWB-based localisation algorithm processed experimental received UWB pulses to detect their leading edges (LE) that were used to derive Time Difference of Arrival (TDoA) data. In turn TDoA data were converted into distances and used to compute the locations of the sensor nodes. Nevertheless, the process of detecting the LEs caused significant errors in the localisation process. To deal with this problem new automated adaptive LE detection methods were derived that succeeded in reducing localisation errors by half, compared to the prototype method, reaching accuracies of ±2cm. Thorough analysis of TDoA profiles revealed that these follow specific trends depending on the positions of the sensor nodes. A number of properties of TDoA profiles are proved mathematically and incorporated into seven localisation algorithms. These algorithms were examined using experimental TDoA data and shown to achieve average localisation errors up to 3cm. Network-based localisation was examined at a later stage of this research since complexities of large scale measurements and difficulties with equipment, delayed acquiring experimental data. The deployed network consisted of a number of nodes whose positions were known (anchors) that were used to estimate the positions of sensor nodes whose positions where considered to be unknown. Localisation was based on received signal strength (RSS) data, at every node to be localised, in anticipation that RSS could provide distance information that could be used in the localisation procedure. Nevertheless, fluctuations in RSS only allowed using localisation algorithms that associated RSS to the positions of anchors. The average localisation error in the network-based localisation algorithms was between 30cm to 100cm.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:568593 |
| Date | January 2013 |
| Creators | Antoniou, Michalis |
| Contributors | Green, Peter |
| Publisher | University of Manchester |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | https://www.research.manchester.ac.uk/portal/en/theses/localisation-of-wireless-sensor-nodes-in-confined-industrial-processes(74bd1acf-5e09-4daf-91ee-a82cb0263a6d).html |
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