Similar to many technological developments, wireless sensor networks have emerged from military needs and found its way into civil applications. Today, wireless sensor networks has become a key technology for diﬀerent types of ”smart environments”, and an intense research eﬀort is currently underway to enable the application of wireless sensor networks for a wide rangeof industrial problems. Wireless networks are of particular importance whena large number of sensor nodes have to be deployed, and/or in hazardous situations.
Localization is important when there is an uncertainty of the exact location of some ﬁxed or mobile devices. One example has been in the supervision of humidity and temperature in forests and/or ﬁelds, where thousands of sensors are deployed by a plane, giving the operator little or no possibility to inﬂuence the precise location of each node. An eﬀective localization algorithm can then use all the available information from the wireless sensor nodes to infer the position of the individual devices. Another application is the positioning of a mobile robot based on received signal strength from a set of radio beacons placed at known locations on the factory ﬂoor.
This thesis work is carried out on the wireless automation testbed at the S3. Focusing on localization processes, we will ﬁrst give an overview of the state of the art in this area. From the various techniques, one idea was found to have signiﬁcant bearing for the development of a new algorithm. We present analysis and simulations of the algorithms, demonstrating improved accuracy compared to other schemes although the accuracy is probably not good enough for some high-end applications. A third aspect of the work concerns the feasibility of approaches based on received signal strength indication (RSSI). Multiple measurement series have been collected in the lab with the MoteIV wireless sensor node platform. The measurement campaign indicates signiﬁcant ﬂuctuations in the RSSI values due to interference and limited repeatability of experiments, which may limit the reliability of many localization schemes, especially in an indoor environment.
2005. , 71 p.