A Robust Received Signal Strength Based Positioning Algorithm for Indoor Environments

Localization for mobile wireless sensor networks has been intensively studied in recent years due to its many applications in mobile networking as well as various public safety problems. However, the complexity of indoor radio propagation, especially when considering mobile users, makes indoor positioning a challenging task. This is mainly due to the severe multipath phenomenon where multiple copies of the transmitted signal are received from many directions (i.e. reflections, diffractions and scattering). A simple approach is to have all mobile nodes equipped with a Global Positioning System (GPS). This cannot be implemented in an indoor environment, where walls and other obstacles obstruct view of the GPS satellites. Moreover, this approach might not be economically feasible due to the size, cost, and power consumption constraints of sensor nodes. Generally, in sensor networks, a small portion of nodes, called beacon or reference nodes are aware of their own positions. Positions of other nodes are determined through some interaction with these reference nodes. For example, in range-based positioning, a mobile node first estimates its distance to all (or some) of the reference nodes, and then calculates its position by using algorithms such as Multilateration. Techniques based on the Received Signal Strength (RSS) ([1],[2]) have been extensively studied in the literature. These techniques, although less accurate compared to more complex range-based techniques, are very simple to implement and offer low cost and effective alternatives for some applications. The core idea is to establish a relation between the received signal