scholarly journals Indoor Pedestrian Self-Positioning Based on Image Acoustic Source Impulse Using a Sensor-Rich Smartphone

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4143 ◽  
Author(s):  
Xiyu Song ◽  
Mei Wang ◽  
Hongbing Qiu ◽  
Liyan Luo
Keyword(s):  
Error Probability ◽  
Low Cost ◽  
Dead Reckoning ◽  
Mobile User ◽  
Acoustic Source ◽  
Environmental Disturbances ◽  
First Order ◽  
Median Error ◽  
Pedestrian Dead Reckoning ◽  
Echo Delay

The ubiquity of sensor-rich smartphones provides opportunities for a low-cost method to track indoor pedestrians. In this situation, pedestrian dead reckoning (PDR) is a widely used technology; however, its cumulative error seriously affects its accuracy. This paper presents a method of combining infrastructure-free indoor acoustic self-positioning with PDR self-positioning, which verifies the rationality of PDR results through the acoustic constraint between a sound source and its image sources. We further determine the first-order echo delay measurements, thus obtaining the mobile user position. We verify that the proposed method can achieve a continuous self-positioning median error of 0.19 m, and the error probability below 0.12 m is 54.46%, which indicates its ability to eliminate PDR error, as well as its adaptability to environmental disturbances.

A Robust Pedestrian Dead Reckoning System Using Low-Cost Magnetic and Inertial Sensors

2019 ◽  
Vol 68 (8) ◽  
pp. 2996-3003 ◽  
Author(s):  
Ling-Feng Shi ◽  
Yu-Le Zhao ◽  
Gong-Xu Liu ◽  
Sen Chen ◽  
Yue Wang ◽  
...  
Keyword(s):  
Inertial Sensors ◽  
Low Cost ◽  
Dead Reckoning ◽  
Pedestrian Dead Reckoning

scholarly journals Drift Control of Pedestrian Dead Reckoning (PDR) for Long Period Navigation under Different Smartphone Poses

2021 ◽  
Vol 10 (1) ◽  
pp. 21
Author(s):  
Ahmed Mansour ◽  
Wu Chen ◽  
Huan Luo ◽  
Yaxin Li ◽  
Jingxian Wang ◽  
...  
Keyword(s):  
Inertial Sensors ◽  
Low Cost ◽  
Dead Reckoning ◽  
Field Measurements ◽  
Step Length ◽  
Detection Algorithm ◽  
Long Period ◽  
Walking Pattern ◽  
Heading Estimation ◽  
Pedestrian Dead Reckoning

The inherent errors of low-cost inertial sensors cause significant heading drift that accumulates over time, making it difficult to rely on Pedestrian Dead Reckoning (PDR) for navigation over a long period. Moreover, the flexible portability of the smartphone poses a challenge to PDR, especially for heading determination. In this work, we aimed to control the PDR drift under the conditions of the unconstrained smartphone to eventually enhance the PDR performance. To this end, we developed a robust step detection algorithm that efficiently captures the peak and valley events of the triggered steps regardless of the device’s pose. The correlation between these events was then leveraged as distinct features to improve smartphone pose detection. The proposed PDR system was then designed to select the step length and heading estimation approach based on a real-time walking pattern and pose discrimination algorithm. We also leveraged quasi-static magnetic field measurements that have less disturbance for estimating reliable compass heading and calibrating the gyro heading. Additionally, we also calibrated the step length and heading when a straight walking pattern is observed between two base nodes. Our results showed improved device pose recognition accuracy. Furthermore, robust and accurate results were achieved for step length, heading and position during long-term navigation under unconstrained smartphone conditions.

scholarly journals A Pedestrian Dead Reckoning System Integrating Low - Cost MEMS Inertial Sensors and GPS Receiver

2014 ◽  
Vol 7 (2) ◽  
pp. 197-203 ◽  
Author(s):  
Jin - feng Li ◽  
◽  
Qing - hui Wang ◽  
Xiao - mei Liu ◽  
Shun Cao ◽  
...  
Keyword(s):  
Inertial Sensors ◽  
Low Cost ◽  
Dead Reckoning ◽  
Gps Receiver ◽  
Pedestrian Dead Reckoning

Comparison of EMG-based and Accelerometer-based Speed Estimation Methods in Pedestrian Dead Reckoning

2011 ◽  
Vol 64 (2) ◽  
pp. 265-280 ◽  
Author(s):  
Wei Chen ◽  
Ruizhi Chen ◽  
Xiang Chen ◽  
Xu Zhang ◽  
Yuwei Chen ◽  
...  
Keyword(s):  
Low Cost ◽  
Estimation Method ◽  
Dead Reckoning ◽  
Field Tests ◽  
Human Locomotion ◽  
Estimation Methods ◽  
Speed Estimation ◽  
Navigation Systems ◽  
Emg Signal ◽  
Pedestrian Dead Reckoning

In low-cost self-contained pedestrian navigation systems, traditional Pedestrian Dead Reckoning (PDR) solutions utilize accelerometers to derive the speed as well as the distance travelled, and obtain the walking heading from magnetic compasses or gyros. However, these measurements are sensitive to instrument errors and disturbances from ambient environment. To be totally different from these signals in nature, the electromyography (EMG) signal is a typical kind of biomedical signal that measures electrical potentials generated by muscle contractions from the human body. This kind of signal would reflect muscle activities during human locomotion, so that it can not only be used for speed estimation, but also disclose the azimuth information from the contractions of lumbar muscles when changing the direction of walking. Therefore, investigating how to utilize the EMG signal for PDR is interesting and promising. In this paper, a novel EMG-based speed estimation method is presented, including setup of the EMG equipment, pre-processing procedure, stride detection and stride length estimation. Furthermore, this method suggested is compared with the traditional one based on accelerometers by means of several field tests. The results demonstrate that the EMG-based method is effective and its performance in PDR can be comparable to that of the accelerometer-based method.

scholarly journals Performance Improvement of a Pedestrian Dead Reckoning System using a Low Cost IMU

2013 ◽  
Vol 19 (6) ◽  
pp. 569-575 ◽  
Author(s):  
Yun-Ki Kim ◽  
Jae-Hyun Park ◽  
Hwy-Kuen Kwak ◽  
Sang-Hoon Park ◽  
ChoonWoo Lee ◽  
...  
Keyword(s):  
Performance Improvement ◽  
Low Cost ◽  
Dead Reckoning ◽  
Pedestrian Dead Reckoning

scholarly journals Real-Time Indoor Positioning Approach Using iBeacons and Smartphone Sensors

2020 ◽  
Vol 10 (6) ◽  
pp. 2003 ◽  
Author(s):  
Liu Liu ◽  
Bofeng Li ◽  
Ling Yang ◽  
Tianxia Liu
Keyword(s):  
Real Time ◽  
Low Cost ◽  
Dead Reckoning ◽  
Indoor Positioning ◽  
Reasonable Accuracy ◽  
Positioning Accuracy ◽  
Localization Accuracy ◽  
Positioning Systems ◽  
Smartphone Sensors ◽  
Pedestrian Dead Reckoning

For localization in daily life, low-cost indoor positioning systems should provide real-time locations with a reasonable accuracy. Considering the flexibility of deployment and low price of iBeacon technique, we develop a real-time fusion workflow to improve localization accuracy of smartphone. First, we propose an iBeacon-based method by integrating a trilateration algorithm with a specific fingerprinting method to resist RSS fluctuations, and obtain accurate locations as the baseline result. Second, as turns are pivotal for positioning, we segment pedestrian trajectories according to turns. Then, we apply a Kalman filter (KF) to heading measurements in each segment, which improves the locations derived by pedestrian dead reckoning (PDR). Finally, we devise another KF to fuse the iBeacon-based approach with the PDR to overcome orientation noises. We implemented this fusion workflow in an Android smartphone and conducted real-time experiments in a building floor. Two different routes with sharp turns were selected. The positioning accuracy of the iBeacon-based method is RMSE 2.75 m. When the smartphone is held steadily, the fusion positioning tests result in RMSE of 2.39 and 2.22 m for the two routes. In addition, the other tests with orientation noises can still result in RMSE of 3.48 and 3.66 m. These results demonstrate our fusion workflow can improve the accuracy of iBeacon positioning and alleviate the influence of PDR drifting.

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