Localization with Incompletely Paired Data in Complex Wireless Sensor Network

Localizing sensors based on Received Signal Strength Indicator (RSSI) localization technique in wireless sensor network can be treated as building a mapping between signal and physical spaces, and the mapping is established from a set of given paired signal strengths and physical location data of known sensors. However, in some realistic scenarios, such a set of completely-paired sensor data is not always accessible, which brings a big challenge for localization of sensors. The localization research in such a scenario is currently almost ignored. In this paper, we develop a novel algorithm to tackle this problem in localization with paired as well as many unpaired data by adapting our previously-proposed Locality Correlation Analysis model; the new algorithm is named as Partially Paired Locality Correlation Analysis (PPLCA). Experimental results in both outdoor and indoor environments do show the feasibility and effectiveness of the proposed algorithm.