A Pedestrian Dead-Reckoning System for Walking and Marking Time Mixed Movement Using an SHSs Scheme and a Foot-Mounted IMU

Wu, Yuan; Zhu, Hai-Bing; Du, Qingyun; Tang, Shuming

doi:10.1109/jsen.2018.2884834

Cited by 29 publications

(14 citation statements)

References 23 publications

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“…2) Layouts: The sensors were mounted on a variety of locations on the body. Studies with a single IMU, most frequently mounted the sensor on one of the shoes [33]. Another commonly selected placement was the waist [34].…”

Section: A Sensor Types and Layoutsmentioning

confidence: 99%

“…These infrastructure-independent methods for human localization are mainly based on Pedestrian Dead Reckoning (PDR), whilst utilizing on-body sensors. In navigation, PDR is the process of calculating one's current position by using a previously determined location, and advancing that location over time using known or estimated speeds [33]. Alternatively, course/stride length and direction can be used to determine the current position.…”

Section: Introductionmentioning

confidence: 99%

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Pedestrian Dead Reckoning With Wearable Sensors: A Systematic Review

Hou

Bergmann

2021

IEEE Sensors J.

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Pedestrian Dead Reckoning (PDR) is the process of calculating one's current location by using the previously known position, and advancing that position over time using established or estimated speeds and trajectories (or alternatively stride lengths and directions). PDR plays an important role in modern life, including tracking locations of people and objects whenever GPS is not available. Self-contained PDR systems do not require an infrastructure, thus they can be used for rapid deployment in situations such as search and rescue, disaster relief or medical emergencies. Wearable sensors are often applied in self-contained PDR, but implementation varies in terms of the number, type and location of sensors used. Many algorithms are designed for PDR in order to reduce the error or drift of the final estimate, with various levels of success. There is a lack of comparison between these different methods and this systematic review of PDR for wearable devices provides a comprehensive overview that can inform further design optimizations. The aim of this paper is to assess the quality of all available PDR literature with a focus on wearable sensors. It provides an outline of the state-of-the-art in the field by comparing the accuracy of different sensor layouts and algorithms. Further directions of research are suggested based on these results. This study also highlights the need for more standardised and robust assessment protocols to capture real-world tracking performance of PDR methods.

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Section: A Sensor Types and Layoutsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Pedestrian Dead Reckoning With Wearable Sensors: A Systematic Review

Hou

Bergmann

2021

IEEE Sensors J.

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“…Absolute zero is always not achieved, so the authors applied an extended Kalman filter to estimate errors in inertial measurement. The model showed deficiencies in indicating the position on an inclined floor, minimized with the application of a gyroscope, which updates the zero angular rate or applies a reduction in the heuristic direction [ 45 , 94 ].…”

Section: Indoor Positioning Systemsmentioning

confidence: 99%

A Review of Technologies and Techniques for Indoor Navigation Systems for the Visually Impaired

Simões

Machado

Sales

et al. 2020

Sensors

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Technologies and techniques of location and navigation are advancing, allowing greater precision in locating people in complex and challenging conditions. These advances have attracted growing interest from the scientific community in using indoor positioning systems (IPSs) with a higher degree of precision and fast delivery time, for groups of people such as the visually impaired, to some extent improving their quality of life. Much research brings together various works that deal with the physical and logical approaches of IPSs to give the reader a more general view of the models. These surveys, however, need to be continuously revisited to update the literature on the features described. This paper presents an expansion of the range of technologies and methodologies for assisting the visually impaired in previous works, providing readers and researchers with a more recent version of what was done and the advantages and disadvantages of each approach to guide reviews and discussions about these topics. Finally, we discuss a series of considerations and future trends for the construction of indoor navigation and location systems for the visually impaired.

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“…In [41], the extended Kalman filter is used to calculate the knee angle from an MAPR system. In [42], the heading is estimated by the EKF, Heuristic Heading Reduction, Flat-ground Hypothesis, and Cardinal Heading-Aided Inertial Navigation techniques. In [16], an optimal-enhanced Kalman filter is proposed, in which adaptive parameters are added to the covariance matrix to achieve accurate positioning of pedestrians within an enclosed environment.…”

Section: Introductionmentioning

confidence: 99%

Improved Pedestrian Positioning with Inertial Sensor Based on Adaptive Gradient Descent and Double-Constrained Extended Kalman Filter

Liu

et al. 2020

Complexity

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The Foot-mounted Inertial Pedestrian-Positioning System (FIPPS) based on the Micro-Inertial Measurement Unit (MIMU) is a good choice for the forest fire fighters when the Global Navigation Satellite System is unavailable. Zero Velocity Update (ZUPT) provides a solution for reducing cumulative positioning errors caused by the integral calculation of the inertial navigation. However, the performance of ZUPT is highly affected by the low accuracy and high noise of the MIMU. The accuracy of conventional ZUPT for attitude alignment is reduced by the zero offset of acceleration and the drift of a gyroscope during the standing phase. An initial alignment algorithm based on Adaptive Gradient Descent Algorithm (AGDA) is proposed. In the stepping phase, the extended Kalman filter (EKF) is often used to correct attitude and position in track estimation. However, the measurement noise of the EKF is influenced by the high-frequency acceleration and angular velocity. Thus, the accuracy of the attitude and position will decrease. A double-constrained extended Kalman filtering (DEKF) is proposed. An adaptive parameter positively correlated with the acceleration and angular velocity is set, and the measurement noise in the DEKF is adaptively adjusted. The performance of the proposed method is verified by implementing the pedestrian test trajectory using MPU-9150 MIMU manufactured by InvenSense. The results show that the attitude error of the AGDA is 33.82% less than that of the conventional GDA. The attitude error of DEKF is 21.70% less than that of the conventional EKF. The experimental results verify the effectiveness and applicability of the proposed method.

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A Pedestrian Dead-Reckoning System for Walking and Marking Time Mixed Movement Using an SHSs Scheme and a Foot-Mounted IMU

Cited by 29 publications

References 23 publications

Pedestrian Dead Reckoning With Wearable Sensors: A Systematic Review

Pedestrian Dead Reckoning With Wearable Sensors: A Systematic Review

A Review of Technologies and Techniques for Indoor Navigation Systems for the Visually Impaired

Improved Pedestrian Positioning with Inertial Sensor Based on Adaptive Gradient Descent and Double-Constrained Extended Kalman Filter

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