Location System For Wireless Sensor Networks

Withthese systems, sensors, instead of being inside the circuit itself, areinstalled in autonomous circuits. Thus, work on control and measurementcan be distributed, e.g. the measurement of magnitudes over ageographically widespread area. Nevertheless, for the systems describedhere to be economically viable, each node has to have very low costs,both in its design and in its production. The most important advantageof this type of network is that of duplication: with so many sensorsparticipating in the operation of the network, if one fails, anotherwill fulfil the function until the failed item can be replaced.

However,organising co-operation between so many nodes is no easy task. Giventhat all nodes have the same hardware and the same software and,moreover, are limited both in energy consumption and in the capacity ofthe process, the protocols used in these types of networks have to bedesigned to operate in these very special conditions. In the case inquestion, the co-operation processes may be greatly simplified if thelocation of each node is known and how the network is organisedgeographically. The great number of nodes makes it impossible to fixthe position of all these manually; an automated method for each nodeto calculate its own position needs to be found.

In this PhDthesis, a new algorithm for finding the position of the nodes is putforward and developed. To this end, the distances separating the nodesare utilised. However, given that each sensor has to be very economic,the quality of measurement of these distances is not expected to behigh and, consequently, location errors appear. Thus, the algorithmproposed here attempts to calculate the best estimate of the nodeposition, in the knowledge that the distances involved have errors.

Finally,to analyse the results obtained with this algorithm, a simulationplatform has been designed which enables a comparison of theperformance of the method described here with that of other algorithmsput forward in recent years. In this way the computational load imposedat the node can be tested and how the presence of errors affects themeasurements in the result obtained.

Moreover, the algorithm wasimplemented in a real node in order to demonstrate that it can be usedin the environment for which it was designed.