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

Geomatics ◽  
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.

scholarly journals Audio Guide for Visually Impaired People Based on Combination of Stereo Vision and Musical Tones

Sensors ◽  
2019 ◽  
Vol 20 (1) ◽  
pp. 151 ◽  
Author(s):  
Walter C. S. S. Simões ◽  
Yuri M. L. R. Silva ◽  
José Luiz de S. Pio ◽  
Nasser Jazdi ◽  
Vicente F. de Lucena
Keyword(s):  
Stereo Vision ◽  
Dead Reckoning ◽  
Ground Level ◽  
Indoor Navigation ◽  
Linear Filter ◽  
Navigation Systems ◽  
Delivery Time ◽  
Visually Impaired People ◽  
Margin Of Error ◽  
Pedestrian Dead Reckoning

Indoor navigation systems offer many application possibilities for people who need information about the scenery and the possible fixed and mobile obstacles placed along the paths. In these systems, the main factors considered for their construction and evaluation are the level of accuracy and the delivery time of the information. However, it is necessary to notice obstacles placed above the user’s waistline to avoid accidents and collisions. In this paper, different methodologies are associated to define a hybrid navigation model called iterative pedestrian dead reckoning (i-PDR). i-PDR combines the PDR algorithm with a Kalman linear filter to correct the location, reducing the system’s margin of error iteratively. Obstacle perception was addressed through the use of stereo vision combined with a musical sounding scheme and spoken instructions that covered an angle of 120 degrees in front of the user. The results obtained in the margin of error and the maximum processing time are 0.70 m and 0.09 s, respectively, with obstacles at ground level and suspended with an accuracy equivalent to 90%.

An Intelligent Navigation Solution for Land Mobile Location-Based Services

2002 ◽  
Vol 55 (2) ◽  
pp. 225-240 ◽  
Author(s):  
Stephen Scott-Young ◽  
Allison Kealy
Keyword(s):  
Firm Growth ◽  
Spatial Information ◽  
Inertial Sensors ◽  
Low Cost ◽  
Dead Reckoning ◽  
Location Based Services ◽  
Geographical Information ◽  
Navigation Systems ◽  
Navigation Solution ◽  
Lower Accuracy

The increasing availability of small, low-cost GPS receivers has established a firm growth in the production of Location-Based Services (LBS). LBS, such as in-car navigation systems, are not necessarily reliant on high accuracy but a continuous positioning service. When available, the accuracy provided by the standard positioning service (SPS) of 30 metres, 95% of the time is often acceptable. The reality is, however, that GPS does not work in all situations, and it is therefore common to integrate GPS with additional sensors. The use of low-cost inertial sensors alone during GPS signal outage is severely restricted due to the accumulation of errors that is inherent with such dead reckoning (DR) systems. Through the integration of spatial information with real-time positioning sensors, intelligence can be added to the land mobile navigation solution. The information contained within a Geographical Information System (GIS) provides additional observations that can be used to improve the navigation result. With this approach, the solution is not dependent on the performance capabilities of the navigation sensors alone. This enables the use of lower accuracy navigation devices, allowing low-cost systems to provide a sustained, viable navigation solution despite long-term GPS outages. Practical results are presented comparing solutions obtained from a hand-held GPS receiver to a gyroscope and odometer.

scholarly journals Indoor Positioning System Based on Chest-Mounted IMU

Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 420 ◽  
Author(s):  
Chuanhua Lu ◽  
Hideaki Uchiyama ◽  
Diego Thomas ◽  
Atsushi Shimada ◽  
Rin-ichiro Taniguchi
Keyword(s):  
Particle Filtering ◽  
Dead Reckoning ◽  
Type Systems ◽  
Indoor Navigation ◽  
Location Based Services ◽  
Upper Body ◽  
Measurement Unit ◽  
Navigation Systems ◽  
3D Navigation ◽  
Zero Velocity

Demand for indoor navigation systems has been rapidly increasing with regard to location-based services. As a cost-effective choice, inertial measurement unit (IMU)-based pedestrian dead reckoning (PDR) systems have been developed for years because they do not require external devices to be installed in the environment. In this paper, we propose a PDR system based on a chest-mounted IMU as a novel installation position for body-suit-type systems. Since the IMU is mounted on a part of the upper body, the framework of the zero-velocity update cannot be applied because there are no periodical moments of zero velocity. Therefore, we propose a novel regression model for estimating step lengths only with accelerations to correctly compute step displacement by using the IMU data acquired at the chest. In addition, we integrated the idea of an efficient map-matching algorithm based on particle filtering into our system to improve positioning and heading accuracy. Since our system was designed for 3D navigation, which can estimate position in a multifloor building, we used a barometer to update pedestrian altitude, and the components of our map are designed to explicitly represent building-floor information. With our complete PDR system, we were awarded second place in 10 teams for the IPIN 2018 Competition Track 2, achieving a mean error of 5.2 m after the 800 m walking event.

scholarly journals Indoor positioning based on foot-mounted IMU

2015 ◽  
Vol 63 (3) ◽  
pp. 629-634 ◽  
Author(s):  
H. Guo ◽  
M. Uradzinski ◽  
H. Yin ◽  
M. Yu
Keyword(s):  
Sensor Fusion ◽  
Dead Reckoning ◽  
Indoor Positioning ◽  
Indoor Navigation ◽  
Navigation Systems ◽  
Initial Alignment ◽  
Step Detection ◽  
Accumulated Error ◽  
Pedestrian Dead Reckoning ◽  
Average Position

Abstract The paper presents the results of the project which examines the level of accuracy that can be achieved in precision indoor positioning by using a pedestrian dead reckoning (PDR) method. This project is focused on estimating the position using step detection technique based on foot-mounted IMU. The approach is sensor-fusion by using accelerometers, gyroscopes and magnetometers after initial alignment is completed. By estimating and compensating the drift errors in each step, the proposed method can reduce errors during the footsteps. There is an advantage of the step detection combined with ZUPT and ZARU for calculating the actual position, distance travelled and estimating the IMU sensors’ inherent accumulated error by EKF. Based on the above discussion, all algorithms are derived in detail in the paper. Several tests with an Xsens IMU device have been performed in order to evaluate the performance of the proposed method. The final results show that the dead reckoning positioning average position error did not exceed 0.88 m (0.2% to 1.73% of the total traveled distance – normally ranges from 0.3% to 10%), what is very promising for future handheld indoor navigation systems that can be used in large office buildings, malls, museums, hospitals, etc.

scholarly journals RETHINKING INDOOR LOCALIZATION SOLUTIONS TOWARDS THE FUTURE OF MOBILE LOCATION-BASED SERVICES

2017 ◽  
Vol IV-4/W4 ◽  
pp. 235-247 ◽  
Author(s):  
C. Guney
Keyword(s):  
Indoor Localization ◽  
Smart Cities ◽  
Indoor Navigation ◽  
Location Based Services ◽  
Outdoor Environment ◽  
Indoor Environments ◽  
Navigation Systems ◽  
Positioning Systems ◽  
Indoor Location ◽  
High Level

Satellite navigation systems with GNSS-enabled devices, such as smartphones, car navigation systems, have changed the way users travel in outdoor environment. GNSS is generally not well suited for indoor location and navigation because of two reasons: First, GNSS does not provide a high level of accuracy although indoor applications need higher accuracies. Secondly, poor coverage of satellite signals for indoor environments decreases its accuracy. So rather than using GNSS satellites within closed environments, existing indoor navigation solutions rely heavily on installed sensor networks. There is a high demand for accurate positioning in wireless networks in GNSS-denied environments. However, current wireless indoor positioning systems cannot satisfy the challenging needs of indoor location-aware applications. Nevertheless, access to a user’s location indoors is increasingly important in the development of context-aware applications that increases business efficiency. In this study, how can the current wireless location sensing systems be tailored and integrated for specific applications, like smart cities/grids/buildings/cars and IoT applications, in GNSS-deprived areas.

scholarly journals Gravity-Based Methods for Heading Computation in Pedestrian Dead Reckoning

Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 1170 ◽  
Author(s):  
Adi Manos ◽  
Itzik Klein ◽  
Tamir Hazan
Keyword(s):  
Field Experiments ◽  
Dead Reckoning ◽  
Vertical Direction ◽  
Indoor Navigation ◽  
Magnetic Sensors ◽  
Dominant Factor ◽  
Heading Estimation ◽  
Using Data ◽  
Pedestrian Dead Reckoning ◽  
Gravity Direction

One of the common ways for solving indoor navigation is known as Pedestrian Dead Reckoning (PDR), which employs inertial and magnetic sensors typically embedded in a smartphone carried by a user. Estimation of the pedestrian’s heading is a crucial step in PDR algorithms, since it is a dominant factor in the positioning accuracy. In this paper, rather than assuming the device to be fixed in a certain orientation on the pedestrian, we focus on estimating the vertical direction in the sensor frame of an unconstrained smartphone. To that end, we establish a framework for gravity direction estimation and highlight the important role it has for solving the heading in the horizontal plane. Furthermore, we provide detailed derivation of several approaches for calculating the heading angle, based on either the gyroscope or the magnetic sensor, all of which employ the estimated vertical direction. These various methods—both for gravity direction and for heading estimation—are demonstrated, analyzed and compared using data recorded from field experiments with commercial smartphones.

PDR-Aided Algorithm with WiFi Fingerprint Matching for Indoor Localization

2014 ◽  
Vol 701-702 ◽  
pp. 989-993
Author(s):  
Wen Bin Yu ◽  
Peng Li ◽  
Zhi Chen ◽  
Chang Li
Keyword(s):  
Social Network ◽  
Indoor Localization ◽  
Dead Reckoning ◽  
Location Based Services ◽  
Fingerprint Matching ◽  
Network Applications ◽  
Wireless Signal ◽  
Signal Fluctuation ◽  
Pedestrian Dead Reckoning ◽  
Wifi Fingerprint

Recently, indoor localization is essential to enable location-based services for many mobile and social network applications. Due to fluctuation of the wireless signal, the accuracy of a simple WiFi fingerprint-based localization is not high. In this paper, we first exploit Pedestrian Dead Reckoning (PDR) technology to overcome the problem of the wireless signal fluctuation, then propose a PDR-aided algorithm with WiFi fingerprint matching for indoor localization, which using the PDR technology aided indoor localization. Experiments show that our algorithm has better accuracy than other indoor localization methods.

scholarly journals A FRAMEWORK OF COGNITIVE INDOOR NAVIGATION BASED ON CHARACTERISTICS OF INDOOR SPATIAL ENVIRONMENT

2015 ◽  
Vol XL-4/W5 ◽  
pp. 25-28
Author(s):  
R. Si ◽  
M. Arikawa
Keyword(s):  
Spatial Cognition ◽  
User Interfaces ◽  
Indoor Navigation ◽  
Location Based Services ◽  
Outdoor Environment ◽  
Navigation Systems ◽  
Spatial Environment ◽  
Map Design ◽  
Indoor Navigation System ◽  
Automatic Positioning

People are easy to get confused in indoor spatial environment. Thus, indoor navigation systems on mobile devices are expected in a wide variety of application domains. Limited by the accuracy of indoor positioning, indoor navigating systems are not common in our society. However, automatic positioning is not all about location-based services (LBS), other factors, such as good map design and user interfaces, are also important to satisfy users of LBS. Indoor spatial environment and people’s indoor spatial cognition are different than those in outdoor environment, which asks for different design of LBS. This paper introduces our design methods of indoor navigation system based on the characteristics of indoor spatial environment and indoor spatial cognition.

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