# Improving IMES Localization Accuracy by Integrating Dead Reckoning Information
## 1 Introduction  
Systems providing spatial information have become increasingly important in daily life. The Global Positioning System (GPS), which is considered a standard outdoor positioning method, is widely used in many commercial applications, such as outdoor gear, car navigation systems and automatic vehicle control. However, these devices do not have sufficient accuracy for use in indoor environments, because the radio signals from satellites are attenuated and scattered by walls, roofs and other objects [1; 2]. In recent years, the indoor positioning problem has attracted increasing research attention because of the strong demand for indoor location-based services, such as pedestrian tracking, navigation and advertisement [3; 4; 5]. Many studies have focused on indoor positioning systems using radio signal strength information [6; 7; 8; 9]. Establally, commercially available indoor positioning systems include the WiFi fingerprinting method [10; 11] and \"iBeacon\" the WiFi fingerprinting method uses received signal strength (RSS) information from a WiFi radio to identify a receiver location. The advantage of this method is that in many cities, numerous WiFi access points have already been installed, and these canbe used as infrastructure for the positioning system. This method provides positioning accuracy of a few meters by finding the best matched pattern between the current received RSS and a pre-built RSS map, which might show a unique pattern in each location. \"iBeacon\", which has been developed by Apple Inc., uses Bluetooth low energy (BLE) technology. Apple Inc. has provided an application program interface (API) for iPhone developers to access iBeacon functions, thus enabling them to easily create new services using indoor position information. The Japan Aerospace Exploration Agency has developed a radio-based indoor positioning system called the \"Indoor Messaging System (IMES)\" [12; 13]. IMES has been developed as a part of the Quasi-Zenith Satellite System (QZSS), and it consists of transmitters that simply broadcast their fixed position as a GPS-compatible signal. Mobile devices that receive the IMES signal can directly decode the position information within the signal reception area (10-20 m in diameter). This positioning method is called \"proximity detection\" or \"range free\". Since the receivers neither calculate the distance from the transmitters nor do the trilateration, like GPS, the positioning is stable, even in indoor environments where multipath interference frequently occurs. Another advantage of IMES is that GPS receivers, the most prevalent devices used for outdoor positioning, can be used with minor firmware modifications because IMES uses a GPS-compatible signal. However, IMES has a disadvantage in that the positioning accuracy is low. Because of the nature of the proximity detection, the positioning accuracy is half of the installation interval of the transmitters; it is usually 5-10 m. This positioning accuracy restricts the applications. Pedestrian dead reckoning (PDR) is another possible solution to realize indoor positioning [14; 15; 16; 17]. In PDR, the relative displacement in each time interval is calculated using an inertial measurement unit (IMU), such as an accelerometer, gyroscope or even a magnetometer. The absolute displacement can be obtained by accumulating these relative displacements from the location where recording is started. PDR is easy to implement on mobile devices, because the above-mentioned IMUs are common in most smartphones, and no external infrastructure is required; furthermore, calculating the location update is relatively simple. However, a simple PDR solution cannot be used in commercial services, because the measurement error in each time interval is accumulated, and so, the tracking error worsens over time. Furthermore, the initial location should be specified to calculate the absolute displacement, and the localization accuracy depends on this initial information.