# A Hybrid Marker-Based Indoor Positioning System for Pedestrian Tracking in Subway Stations
## 1 Introduction  
In recent times, subway stations have evolved into increasingly complex spatial structures. This has been caused by the connection of adjacent buildings, special expansion for various activities such as shopping, tourism, meetings, and meals as well as an increase in the number of platforms for train use. These environmental changes have accelerated the need for indoor navigation systems in subway stations to support mobility and increase user convenience, particularly for the underprivileged. To provide indoor navigation services at subway stations, several issues need to be solved, such as the accuracy of location information, the cost of building indoor maps, and the maintenance of infrastructure such as Wi-Fi. Unlike ordinary buildings, subway stations have a structure in the form of an open space with high floor height. This structure results in a decrease in positioning accuracy when positioning methods that utilize a characteristic in which the strength of a signal varies due to walls and obstacles, such as Wi-Fi-based positioning, is used. In addition, various issues need to be addressed, such as radio interference problems caused by the entry and exit of trains, infrastructure installation problems, frequent internal facility changes in subway stations, and the maintenance costs of railroad operating institutions. Consequently, in order to provide indoor navigation services in subway stations, there is a need for a plan that can solve these issues and appropriately apply the solutions. Indoor positioning technologies for providing indoor navigation services are themselves very diverse. Using Wi-Fi or Bluetooth technologies, typical indoor positioning techniques make use ofnatural phenomena such as geomagnetic data, and inertial measurement unit (IMU) sensors installed in smart devices. Such resources are used for absolute positioning, which calculates the location of an object or person in fixed coordinates, and for relative positioning, which tracks changes in relative position. Absolute positioning enables a reasonably accurate position calculation because the distribution of signals can be learned in advance or a large amount of data can be gathered when learning data are collected in the offline phase. However, when IMU sensors are used for relative positioning, errors may accumulate due to sensor biases and fluctuations, and therefore an appropriate response to these errors is required. One of the methods for estimating the absolute location of the user is fingerprinting-based positioning. The fingerprinting method compares a received signal strength list measured at the positioning time with a signal map constructed during the training phase to determine the position of a device on the signal map. Among the devices that can be applied to the fingerprinting method are Wi-Fi [1; 2], Bluetooth [3; 4], and magnetometer sensors [5]. In particular, the fingerprinting method is widely used in commercial Wi-Fi positioning systems, and many methods for overcoming disadvantages such as an increase in collection costs are being actively studied [6]. However, the multilateration method uses the received signal strength or roundtrip time of the signal. The received-signal-strength-based multilateration positioning means that the received signal strength is converted into a distance using signal propagation modeling, and then the device location is calculated from the distance information of a plurality of transmitting device connection points. The round-trip-time-based multilateration of the signal removes the delay time at the transmission signal connection point from the pulse request time to the transmission signal connection point and the difference of the pulse arrival time from the device after the round trip. Subsequently, the result is converted into a distance to perform multilateration positioning [7]. In addition to Wi-Fi, many other technologies such as the GPS, WSNs [8], and cellular networks [9], use this approach. In particular, the GPS module is widely used for outdoor positioning.