Classifying Elevators and Escalators in 3D Pedestrian Indoor Navigation Using Foot-Mounted Sensors

Results of an experimental study of a local navigation system based on the processing signals from broadcast sources presented. The results of the development of processing algorithms for point-to-point coordinates estimation of the object are presented. The results of the development of algorithms for trajectories estimation are presented. In performed simulation the possibility of obtaining submeter position estimation accuracy in the proposed system is shown. Development results of the navigation module demonstrator are presented. The results of experimental work in difficult navigation conditions, in the presence of shading, reflections and other factors, are presented. It is shown that the developed navigation module allows in the open space near buildings which partially obscuring the satellite systems signals to obtain accuracy higher than the GNSS navigation equipment. In indoor environment in the absence of satellite navigation signals, the developed module shows positioning accuracy not worse than 1.5 meters and provides a measurement rate 1 Hz and better.

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Intelligent Vision Impaired Indoor Navigation Using Visible Light Communication

Technological Trends in Improved Mobility of the Visually Impaired - EAI/Springer Innovations in Communication and Computing ◽

10.1007/978-3-030-16450-8_8 ◽

2019 ◽

pp. 181-206 ◽

Cited By ~ 1

Author(s):

Jayakody Arachchilage Don Chaminda Jayakody ◽

Iain Murray ◽

Johannes Hermann ◽

Shashika Lokuliyana ◽

Vandhana Dunuwila

Keyword(s):

Visible Light ◽

Visible Light Communication ◽

Indoor Navigation

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S-PDR: SBAUPT-Based Pedestrian Dead Reckoning Algorithm for Free-Moving Handheld Devices

Geomatics ◽

10.3390/geomatics1020010 ◽

2021 ◽

Vol 1 (2) ◽

pp. 148-176

Author(s):

Maan Khedr ◽

Naser El-Sheimy

Keyword(s):

Smart Cities ◽

Dead Reckoning ◽

Human Motion ◽

Indoor Navigation ◽

Location Based Services ◽

Navigation Systems ◽

Short Term ◽

Navigation Solution ◽

Correction Technique ◽

Pedestrian Dead Reckoning

Mobile location-based services (MLBS) are attracting attention for their potential public and personal use for a variety of applications such as location-based advertisement, smart shopping, smart cities, health applications, emergency response, and even gaming. Many of these applications rely on Inertial Navigation Systems (INS) due to the degraded GNSS services indoors. INS-based MLBS using smartphones is hindered by the quality of the MEMS sensors provided in smartphones which suffer from high noise and errors resulting in high drift in the navigation solution rapidly. Pedestrian dead reckoning (PDR) is an INS-based navigation technique that exploits human motion to reduce navigation solution errors, but the errors cannot be eliminated without aid from other techniques. The purpose of this study is to enhance and extend the short-term reliability of PDR systems for smartphones as a standalone system through an enhanced step detection algorithm, a periodic attitude correction technique, and a novel PCA-based motion direction estimation technique. Testing shows that the developed system (S-PDR) provides a reliable short-term navigation solution with a final positioning error that is up to 6 m after 3 min runtime. These results were compared to a PDR solution using an Xsens IMU which is known to be a high grade MEMS IMU and was found to be worse than S-PDR. The findings show that S-PDR can be used to aid GNSS in challenging environments and can be a viable option for short-term indoor navigation until aiding is provided by alternative means. Furthermore, the extended reliable solution of S-PDR can help reduce the operational complexity of aiding navigation systems such as RF-based indoor navigation and magnetic map matching as it reduces the frequency by which these aiding techniques are required and applied.

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