Indoor localization based on radio interferometric positioning system

Abstract

Finding location plays a significant role in many applications such as car navigation systems, product tracking in the warehouse, and failure detections of the buildings. Objects to be localized are often resource-limited, and thus low computational complexity and implementation cost are desirable. Moreover, multipath effects make accurate localization in indoor areas a difficult task. To meet these challenges, we develop accurate indoor localization systems based on radio interferometric positioning system (RIPS). The RIPS measures the phase of interfering sinusoidal signals to obtain the range estimates, and it has shown a potential to yield highly accurate location information at low-computational complexity. Yet, it has several drawbacks, including sensitivity to multipath and integer ambiguity issues. In this dissertation, we first design a receiver for the RIPS using undersampling techniques to circumvent the noise augmentation problem. We perform theoretical analysis of both the original and proposed RIPS by deriving the Cram\'{e}r-Rao Lower Bounds (CRLBs) of the range and location estimates, considering white and colored noise. The systems are also implemented on National Instruments' Universal Software Radio Peripherals (NI USRPs) for experimental analysis. The second part of this dissertation focuses on designing indoor localization systems based on the RIPS using millimeter wave (MMW) signaling. We utilize space-time coding (STC) to achieve robustness to multipath and avoid integer ambiguities. The efficiency of the proposed systems is confirmed through simulations and experiments.