Error Modeling and Estimation Fusion for Indoor Localization
There has been much interest in offering multimedia Location-Based Service (LBS) to indoor users (e.g., sending video/audio streams according to user locations). Offering good LBS largely depends on accurate indoor localization of mobile stations (MSs). To achieve that, in this paper, the authors first model and analyze the error characteristics of important indoor localization schemes, using Radio Frequency IDentification (RFID) and Wi-Fi. Their models are simple to use, capturing important system parameters and measurement noises, and quantifying how they affect the accuracies of the localization. Given that there have been many indoor localization techniques deployed; an MS may receive simultaneously multiple co-existing estimations on its location.