# Indoor Carrier Phase Positioning Technology Based on OFDM System
## 1 Introduction
The ranging principle of pseudorandom code mode is similar to TOA, and the measurement error of pseudorandom code mode is vast. The carrier phase ranging method uses the carrier phase of the measurement signal to extract the propagation distance information. Under line-of-sight (LOS) conditions, the carrier phase's measurement error is a small fraction of the carrier wavelength and can reach the centimeter range. However, the carrier phase measurement includes unknown integer ambiguity: the distance between the user and the BS in terms of carrier wavelength can be divided into an integral part of the wavelength plus a fractional function. During the initialization of positioning, the phase measurement is in the range \([0,2\pi]\), so only fractional multiples of the distance can be measured, which causes the problem of integer ambiguity. Once this problem is solved, the carrier phase positioning can meet the requirements of high accuracy. Inspired by reference [19], the positioning accuracy might be significantly improved if the carrier phase technology can be extended in the indoor location system. Compared with GNSS positioning, wireless networks can work in challenging scenarios and have more flexible carrier frequency configurations, fewer error sources, and more minor path losses. These characteristics constitute the advantages of supporting carrier phase technology in wireless networks. However, despite these advantages, there are many challenges while applying carrier phase positioning in wireless networks: Multipath and NLOS propagation in the indoor environment, fast resolution of integer ambiguities in wireless networks, etc. In summary, this paper proposes a carrier phase-ranging scheme based on the OFDM system. Under the premise of high accuracy ranging, this paper focuses on two aspects: carrier phase measurement in a multipath environment and how to solve the integer ambiguity quickly and accurately. First, we model the carrier phase measurement in a multipath environment and analyze the integer ambiguity generation. Second, we propose an extended Kalman filter (EKF) for solving the integer ambiguity. The EKF-based algorithm can solve the position of the terminal while solving the integer ambiguity. Further, we describe how to utilize the EKF to mitigate the errors caused by NLOS propagation. The overall structure of this study contains five chapters. Section 2 describes the model for studying TOA and phase estimation in OFDM systems. In Section 3, we propose an EKF that combines carrier phase and TOA measurements to enhance positioning accuracy and reduce the impact of NLOS error on mobile positioning. Numerical simulation results are presented in Section 4 to prove the effectiveness of the new methods. In Section 5, we summarize conclusions drawn from this paper. In this paper, vectors and matrices are denoted by boldface lower-case letters and boldface upper-case letters. The superscript \([. ]^{T}\) denotes the transpose. The superscript \([. ]^{ij}\) and the subscript \([. ]_{ab}\) represent, respectively, the single-difference (SD) between the transmitters and between the receivers.