Map matching and heuristic elimination of gyro drift for personal navigation systems in GPS-denied conditions

Aggarwal, Priyanka; Thomas, D.W.P.; Ojeda, Lauro; Borenstein, J.

doi:10.1088/0957-0233/22/2/025205

Cited by 45 publications

(11 citation statements)

References 22 publications

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“…When the error of the gyroscope is significant, and if left uncorrected, it can make the entire PDR system unusable. Map-matching is the process of comparing the pedestrian's trajectory data with a digital map of the environment to match the trajectory data to the route segment on which the pedestrian is walking, and it can be used to correct the heading error of a PDR system [63]. Unlike previous map-matching approaches that require the use of a detailed scaled map ( i.e.…”

Section: Gyroscope Error Calibration With Map Matchingmentioning

confidence: 99%

On Calibrating the Sensor Errors of a PDR-Based Indoor Localization System

Lan

Shih

2013

Sensors

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Many studies utilize the signal strength of short-range radio systems (such as WiFi, ultrasound and infrared) to build a radio map for indoor localization, by deploying a large number of beacon nodes within a building. The drawback of such an infrastructure-based approach is that the deployment and calibration of the system are costly and labor-intensive. Some prior studies proposed the use of Pedestrian Dead Reckoning (PDR) for indoor localization, which does not require the deployment of beacon nodes. In a PDR system, a small number of sensors are put on the pedestrian. These sensors (such as a G-sensor and gyroscope) are used to estimate the distance and direction that a user travels. The effectiveness of a PDR system lies in its success in accurately estimating the user's moving distance and direction. In this work, we propose a novel waist-mounted based PDR that can measure the user's step lengths with a high accuracy. We utilize vertical acceleration of the body to calculate the user's change in height during walking. Based on the Pythagorean Theorem, we can then estimate each step length using this data. Furthermore, we design a map matching algorithm to calibrate the direction errors from the gyro using building floor plans. The results of our experiment show that we can achieve about 98.26% accuracy in estimating the user's walking distance, with an overall location error of about 0.48 m.

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Section: Gyroscope Error Calibration With Map Matchingmentioning

confidence: 99%

On Calibrating the Sensor Errors of a PDR-Based Indoor Localization System

Lan

Shih

2013

Sensors

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“…In the course of project implementation the algorithm was developed that allows making correction of MEMS sensors positioning error based on the information about expectable paths of user's movement. After sensors detect users turning movement the search of the nearest turn on the floor plan in the specified direction is performed [10]. The found turn makes it possible to correct positioning.…”

Section: Movement Monitoring With the Use Of Building Floor Planmentioning

confidence: 99%

Method monitoring of movement in the task of indoor navigation

Osipov¹,

Andreev²

2018

Collection of Selected Papers of the IV International Conference on Information Technology and Nanotechnology

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“…In view of these evidences, many authors have declared that the Earth magnetic field is not useful indoors [8], so they better relay on: higher quality IMUs (also bulkier and more costly), other external sensors (Local Positioning Systems, also known as LPS [9], [10]), or some heuristics (e.g. HDE, Mapmatching) in order to avoid the use of magnetometers.…”

Section: A Limitations Of Magnetic Compassingmentioning

confidence: 99%

Improved heuristic drift elimination with magnetically-aided dominant directions (MiHDE) for pedestrian navigation in complex buildings

Jiménez

Seco

Zampella

et al. 2012

Journal of Location Based Services

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Abstract-The main problem of Pedestrian Dead-Reckoning (PDR) using only a body-attached IMU is the accumulation of heading errors. The heading provided by magnetometers in indoor buildings is in general not reliable and therefore it is commonly not used. Recently, a new method was proposed called Heuristic Drift Elimination (HDE) that minimizes the heading error when navigating in buildings. It assumes that the majority of buildings have their corridors parallel to each other, or they intersect at right angles, and consequently most of the time the person walks along a straight path with a heading constrained to one of four possible directions. In this paper we study the performance of HDE-based methods in complex buildings, i.e. with pathways also oriented at 45°, long curved corridors, and wide areas where non-oriented motion is possible. We explain how the performance of the original HDE method can be deteriorated in complex buildings, and also, how severe errors can appear in case of false matches with the building's dominant directions. Although magnetic compassing indoors has a chaotic behavior, in this paper we analyze large data-sets in order to study the potential use that magnetic compassing has to estimate the absolute yaw angle of a walking person. Apart from these analysis, this paper also proposes an improved HDE method called MiHDE (Magnetically-aided Improved Heuristic Drift Elimination), that is implemented over a PDR framework that uses foot-mounted inertial navigation with an Extended Kalman Filter (EKF). The EKF is fed with the MiHDE-estimated orientation error, gyro bias corrections, as well as the confidence over that corrections. We experimentally evaluated the performance of the proposed MiHDE-based PDR method, comparing it with the original HDE implementation. Results show that both methods perform very well in ideal orthogonal narrow-corridor buildings, and MiHDE outperforms HDE for non-ideal trajectories (e.g. curved paths) and also makes it robust against potential false dominant direction matchings.

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Map matching and heuristic elimination of gyro drift for personal navigation systems in GPS-denied conditions

Cited by 45 publications

References 22 publications

On Calibrating the Sensor Errors of a PDR-Based Indoor Localization System

On Calibrating the Sensor Errors of a PDR-Based Indoor Localization System

Method monitoring of movement in the task of indoor navigation

Improved heuristic drift elimination with magnetically-aided dominant directions (MiHDE) for pedestrian navigation in complex buildings

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