# Indoor Carrier Phase Positioning Technology Based on OFDM System
## 1 Introduction  
With the rapid development of industries such as the Internet of Things and industrial control, high-precision indoor positioning technology has become an important issue to be solved. It is challenging to receive valid satellite navigation signals in the indoor environment, and other high-precision positioning technologies need to be studied. In recent years, positioning services based on wireless communications are rapidly developing. The mobile cellular network covers a wide area and is one option for dense urban areas and indoor positioning. Benefit from the advance of 5G technology, high-precision positioning using the wireless access network has become a hot research direction. In wireless networks, traditional ranging-based positioning methods include angle of arrival (AOA), received signal strength (RSS), and time-of-arrival (TOA). Among them, AOA determines location of the user by measuring the angle between the terminal and the base station (BS) [1]. Since measuring angle often requires a sufficient number of antennas at the receiver, the application range of AOA technology is limited. RSS technology needs to establish an accurate signal energy propagation model, making it challenging to achieve high measurement accuracy [2]. TOA-based positioning technology converts arrival time to a distance and then uses the distance information for positioning. TOA has been widely used due to its low requirements of positioning equipment [3]. This paper mainly studies high-precision TOA measurement and positioning algorithms based on orthogonal frequency division multiplex (OFDM) systems. TOA estimation can be considered as a channel estimation problem. Many documents carry out channel impulse response (CIR) estimation from the time domain or frequency domain perspective in the OFDM multi-carrier system [4; 5; 6; 7; 8; 9]. Typical schemes are cross-correlation algorithms based on the pseudo-randomness of the transmission sequence, including the maximum criterion algorithm and the threshold algorithm[4]. However, this positioning method is limited by the signal bandwidth and receiver resolution, and it is challenging to achieve sub-meter accuracy. Besides, TOA-based parameter estimation techniques have been widely studied, including multiple signal classification algorithm (MUSIC) [10], Signal Parameters via Rotational Invariant Techniques (ESPRIT) [11], and Space-Alternating Generalized Expectation maximization (SAGE) [12] algorithms. These algorithms are not limited by the system sampling rate but are determined by the search interval for time delay estimation. A smaller search interval will effectively improve the accuracy of TOA estimation but will significantly increase the computational complexity. The vast computational overhead makes it difficult to apply such algorithms to real-time user localization scenarios. Other studies have attempted to apply phase ranging techniques to indoor localization [13; 14; 15]. However, specific phase emission and measurement devices are challenging to reduce the cost of localization effectively. Phase measurement techniques based on OFDM systems can provide high accuracy positioning measurements while satisfying communication requirements, and therefore are a research direction for phase-based positioning. References [16; 17; 18] describe methods for distance measurement through the phase difference of subcarriers in OFDM systems. Still, such schemes are often only suitable for LOS propagation or multipath propagation when the Rice factor is high. Carrier phase localization techniques based on wireless cellular networks have been proposed in the literatures [19; 20]. Furthermore, carrier phase measurement in multipath environments and the suppression of non-line-of-sight (NLOS) error require further research. There are two modes for receivers in global navigation satellite systems (GNSS): pseudorandom code (C/A code or P-code) and the carrier phase [21; 22].