With the rapid development in pervasive computing and Location-based Services (LBS), location information play an important role in various applications, such as tracking, surveillance, advertising and etc. Further, such location information enable us to infer location-aware information. On the one hand, researches have proposed numbers of approaches that enable localization in indoor environments as GPS does not work well under such circumstances. These approaches mainly fall into two categories, based on RSS measurement and techniques that leverage inertial sensors.On the other hand, after obtaining location information, researchers aim to provide higher level information such as pathway and floor plan by leveraging accurate localization result.

However, all of above have...[ Read more ]

With the rapid development in pervasive computing and Location-based Services (LBS), location information play an important role in various applications, such as tracking, surveillance, advertising and etc. Further, such location information enable us to infer location-aware information. On the one hand, researches have proposed numbers of approaches that enable localization in indoor environments as GPS does not work well under such circumstances. These approaches mainly fall into two categories, based on RSS measurement and techniques that leverage inertial sensors.On the other hand, after obtaining location information, researchers aim to provide higher level information such as pathway and floor plan by leveraging accurate localization result.

However, all of above have several limitations in real practice. First, RSS-based ranging technique suffers from multipath phenomenon and it is not easy to localize multiple objects. Second, inertial sensor based techniques are far from accuracy due to the fact that they all based on step counting and step length vary from person to person. Third, based on location information, researchers focus on how to use sensor reading from smart phone to automatically reconstruct the walking pathway or floor plan and such information is insufficient to provide better services.

To fill in the gap, in this dissertation, I propose several novel techniques that overcome the above limitations. First, I leverage frequency diversity to differentiate Line-of-sight (LOS) path from multipath and I construct LOS radio map that can localize multiple objects based on finger print technique. Third, I improve the localization accuracy of inertial sensor based method by formulating the calculation of displacement as a curve fitting problem. Last, to provide better services, I design and implement a system that achieve floor plan identification by leveraging smart phone sensor reading.