A Method for Adaptive GNSS/PDR Integrated Navigation

Ryoya Shiraiwa, Fumiya Odai, Yukihiro Kubo

Abstract:	In recent years, location-based services (LBS) have attracted much attention. The LBS has been used for social network service (SNS), navigation applications, and so on. These services are expanding in our lifestyle because of increasing smartphone users. Therefore, the demand to acquire accurate location information everywhere is increasing. The technology mainly used for estimating position of smartphone users is the global navigation satellite system (GNSS). However, the satellite positioning has demerit that it cannot provide accurate location information. This is because the number of observable satellites decreases when the signals from satellite are easily blocked by buildings, trees and other obstacles. Other method besides the satellite positioning includes wireless fidelity (Wi-Fi) [1] and bluetooth low energy (BLE) [2]. Wi-Fi and BLE are restricted to a specific location, but pedestrian dead reckoning (PDR) [3] is a method which can be completed only with a device. Therefore, we focus on the indoor/outdoor positioning by GNSS/PDR integrated navigation system. The PDR system is a method to estimate position of pedestrian by using sensors (inertial measurement unit (IMU), magnetic sensor, etc.). PDR has the advantage that it does not require any additional costs besides the device. On the other hand, it has the disadvantage that it sometimes has large errors because of sensor biases and it is difficult to efficiently take into account the walking characteristics of the pedestrian individually.
Published in:	Proceedings of the 36th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2023) September 11 - 15, 2023 Hyatt Regency Denver Denver, Colorado
Pages:	109 - 120
Cite this article:	Shiraiwa, Ryoya, Odai, Fumiya, Kubo, Yukihiro, "A Method for Adaptive GNSS/PDR Integrated Navigation," Proceedings of the 36th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2023), Denver, Colorado, September 2023, pp. 109-120. https://doi.org/10.33012/2023.19380
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