• Journal of Positioning, Navigation, and Timing
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• v.12 no.4
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• pp.399-408
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• 2023

In this paper, we propose a solution that enables continuous indoor/outdoor positioning of smartphone users through the integration of Pedestrian Dead Reckoning (PDR) and GPS/WiFi signals. Considering that accurate step detection affects the accuracy of PDR, we propose a Deep Neural Network (DNN)-based technology to distinguish between walking and non-walking signals such as walking in place. Furthermore, in order to integrate PDR with GPS and WiFi signals, a technique is used to select a proper measurement by distinguishing between indoor/outdoor environments based on GPS Dilution of Precision (DOP) information. In addition, we propose a technology to adaptively change the measurement error covariance matrix by detecting measurement outliers that mainly occur in the indoor/outdoor transition section through a residual-based χ² test. It is verified through experiments on a testbed that these technologies significantly improve the performance of PDR and PDR/GPS/WiFi fingerprinting-based integrated pedestrian navigation.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.3
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• pp.173-182
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• 2015

A real-time, Indoor navigation systems utilize ultra-wide band (UWB), radio-frequency identification (RFID) and received signal strength (RSS) techniques that encompass WiFi, FM, mobile communications, and other similar technologies. These systems typically require surplus infrastructure for their implementation, which results in significantly increased costs and complexity. Therefore, as a solution to reduce the level of cost and complexity, an inertial measurement unit (IMU) and quick response (QR) codes are utilized in this paper to facilitate navigation with the assistance of a smartphone. The QR code helps to compensate for errors caused by the pedestrian dead reckoning (PDR) algorithm, thereby providing more accurate localization. The proposed algorithm having IMU in conjunction with QR code shows an accuracy of 0.64 m which is higher than existing indoor navigation techniques.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.1
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• pp.133-138
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• 2019

The indoor navigation system using smart phone is a very important infrastructure technology for users' location based services in large indoor facilities. For this purpose, if the user can estimate the movement distance and direction by using the acceleration sensor and the gyro sensor built in the smartphone, the additional external environment is not necessary, which is a very useful technique. This paper deals with indoor navigation system technology that uses Pedestrian Dead Reckoning (PDR) technology and Kalman filter on a general smartphone and allows the user to trace the position while moving the smartphone in front of his chest. In particular, an extended Kalman filter was designed to estimate the direction of movement, and its performance was verified when walking at a constant speed.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1491-1496
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• 2009

Because of the development of advanced construction technology, the inner environments of building become more and more complicated, which may result in many problems. The administer may forget where they put up the certain picture, and search for it all over the building, or they underestimate the number of the visitors, and find the situation is out of control, while the pedestrian may get lost, and after making their efforts, they found they turned back to the origin point again. So it is very necessary to establish an indoor spatial database. On one hand, it is able to assist administrator to manage the property and human flow inside the building, on the other hand it could help the pedestrian find the way easily especially when they are not familiar with the building or there is an emergency. This paper focused on how to create the indoor spatial database including both static database and moving objects database. The static database is built on the basis of 3D building models, and the moving objects database gets information from many kinds of cameras and sensors installed in the building. And at the same time the paper discussed the practical use of indoor spatial database mainly in three aspects including consistency management, building restructure, and pedestrian navigation.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.251-256
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• 2006

In the work package 'Integrated Positioning' of the research project NAVIO (Pedestrian Navigation Systems in Combined Indoor/Outdoor Environements) we are dealing with the navigation and guidance of visitors of our University. Thereby start points are public transport stops in the surroundings of the Vienna University of Technology and the user of the system should be guided to certain office rooms or persons. For the position determination of the user different location sensors are employed, i.e., for outdoor positioning GPS and dead reckoning sensors such as a digital compass and gyro for heading determination and accelerometers for the determination of the travelled distance as well as a barometric pressure sensor for altitude determination and for indoor areas location determination using WiFi fingerprinting. All sensors and positioning methods are combined and integrated using a Kalman filter approach. Then an optimal estimate of the current location of the user is obtained using the filter. To perform an adequate weighting of the sensors in the stochastic filter model, the sensor characteristics and their performance was investigated in several tests. The tests were performed in different environments either with free satellite visibility or in urban canyons as well as inside of buildings. The tests have shown that it is possible to determine the user's location continuously with the required precision and that the selected sensors provide a good performance and high reliability. Selected tests results and our approach will be presented in the paper.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.1
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• pp.35-44
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• 2022

In this paper, a dual foot (DF)-PDR system is proposed for the fusion of integration (IA)-based PDR systems independently applied on both shoes. The horizontal positions of the two shoes estimated from each PDR system are fused based on a particle filter. The proposed method bounds the position error even if the walking time increases without an additional sensor. The distribution of particles is a non-Gaussian distribution to express the lateral error due to systematic drift. Assuming that the shoe position is the pedestrian position, the multi-modal position distribution can be fused into one using the Gaussian sum. The fused pedestrian position is used as a measurement of each particle filter so that the position error is corrected. As a result, experimental results show that position of pedestrians can be effectively estimated by using only the inertial sensors attached to both shoes.

• KIISE Transactions on Computing Practices
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• v.23 no.4
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• pp.210-216
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• 2017

In the paper we propose and implement a new indoor localization system where the techniques of magnetic field based fingerprinting and pedestrian dead reckoning are combined. First, we determine a target's location by comparing acquired magnetic field values with a magnetic field map containing pre-collected field values at different locations and choosing the location having the closest value. As the target moves, we use pedestrian dead reckoning to estimate the expected moving path, reducing the maximum positioning error of the initial location. The system eliminates the problem of localization error accumulation in pedestrian dead reckoning with the help of the fingerprinting and does not require Wi-Fi AP infrastructure, enabling cost-effective localization solution.

• Journal of Advanced Navigation Technology
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• v.17 no.6
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• pp.810-815
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• 2013

In case Wi-Fi network based First responder's position tracking system is used, range measurement must be generated from RSSI finger print database. However, it is impossible to build up finger print database and to perform rescue operation at same time in the scene of rescue. In this paper, improvised Wi-Fi network without finger print database and pedestrian dead reckoning based first responders tracking system is proposed.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.1
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• pp.1-9
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• 2007

3D data are in great demand for pedestrian navigation recently. For pedestrian navigation, we needs to reconstruct 3D model in detail from people's eye. In order to present spatial features in detail for pedestrian navigation, it is indispensable to develop 3D model not only in outdoor environment but also in indoor environment such as underground shopping complex. However, it is very difficult to acquire 3D data efficiently by mobile mapping without GPS. In this research, 3D shape was acquired by Laser scanner, and texture by CCD(Charge Coupled Device) sensor. Continuous changes position and attitude of sensors were measured by IMU(Inertial Measurement Unit). Moreover, IMU was corrected by relative orientation of CCD images without GPS(Global Positioning System). In conclusion, Reliable, quick, and handy method for acquiring 3D data for indoor environment is proposed by a combination of a digital camera and a laser scanner with IMU.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.5
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• pp.319-333
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• 2018

As human beings spend more time indoors, and with the growing complexity of indoor spaces, more focus is given to indoor spatial applications and services. 3D topological networks are used for various spatial applications that involve navigation indoors such as emergency evacuation, indoor positioning, and visualization. Manually generating indoor network data is impractical and prone to errors, yet current methods in automation need expensive sensors or datasets that are difficult and expensive to obtain and process. In this research, a methodology for semi-automatically generating a 3D indoor topological model based on IndoorGML (Indoor Geographic Markup Language) is proposed. The concept of Shooting Point is defined to accommodate the usage of omnidirectional images in generating IndoorGML data. Omnidirectional images were captured at selected Shooting Points in the building using a fisheye camera lens and rotator and indoor spaces are then identified using image processing implemented in Python. Relative positions of spaces obtained from CAD (Computer-Assisted Drawing) were used to generate 3D node-relation graphs representing adjacency, connectivity, and accessibility in the study area. Subspacing is performed to more accurately depict large indoor spaces and actual pedestrian movement. Since the images provide very realistic visualization, the topological relationships were used to link them to produce an indoor virtual tour.