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Pedestrian Dead Reckoning with Particle Filter for Handheld Smartphone

Tutkimustuotosvertaisarvioitu

Standard

Pedestrian Dead Reckoning with Particle Filter for Handheld Smartphone. / Collin, Jussi; Perttula, Arto; Parviainen, Jussi; Racko, Jan; Brida, Peter.

2016 International Conference on Indoor Positioning and Indoor Navigation (IPIN). IEEE, 2016.

Tutkimustuotosvertaisarvioitu

Harvard

Collin, J, Perttula, A, Parviainen, J, Racko, J & Brida, P 2016, Pedestrian Dead Reckoning with Particle Filter for Handheld Smartphone. julkaisussa 2016 International Conference on Indoor Positioning and Indoor Navigation (IPIN). IEEE, International Conference on Indoor Positioning and Indoor Navigation, 1/01/00. https://doi.org/10.1109/IPIN.2016.7743608

APA

Collin, J., Perttula, A., Parviainen, J., Racko, J., & Brida, P. (2016). Pedestrian Dead Reckoning with Particle Filter for Handheld Smartphone. teoksessa 2016 International Conference on Indoor Positioning and Indoor Navigation (IPIN) IEEE. https://doi.org/10.1109/IPIN.2016.7743608

Vancouver

Collin J, Perttula A, Parviainen J, Racko J, Brida P. Pedestrian Dead Reckoning with Particle Filter for Handheld Smartphone. julkaisussa 2016 International Conference on Indoor Positioning and Indoor Navigation (IPIN). IEEE. 2016 https://doi.org/10.1109/IPIN.2016.7743608

Author

Collin, Jussi ; Perttula, Arto ; Parviainen, Jussi ; Racko, Jan ; Brida, Peter. / Pedestrian Dead Reckoning with Particle Filter for Handheld Smartphone. 2016 International Conference on Indoor Positioning and Indoor Navigation (IPIN). IEEE, 2016.

Bibtex - Lataa

@inproceedings{ca5e84d6a1c846e59b04b83f2293f2bd,
title = "Pedestrian Dead Reckoning with Particle Filter for Handheld Smartphone",
abstract = "Commonly used Global Navigation Satellite Systems (GNSS) are inappropriate as Location Based Services (LBS) in indoor environment. Therefore research teams are developing different systems, which can be used as a suitable alternative. One of options is to use Inertial Navigation System (INS) which consists of inertial sensors and mathematic procedures. This concept has been known for a long time, but with arrival of Microelectro Mechanical System (MEMS) INS found wide use. Smartphones with inertial sensors, such as accelerometers and gyroscopes, allow us to use them as input devices for Pedestrian Dead Reckoning (PDR). In this paper we present PDR by using smartphone sensors. They can be classified as low-cost Inertial Measurement Unit (IMU), and have been compared with more precise and expensive Xsens IMU. Accuracy of inertial sensors has increased in the past few years, but they still cannot alone provide proper accuracy because of many negative effects, such as heading drift due to gyroscope bias. Particle Filter (PF) has been successfully used with map constraints to increase the accuracy of proposed location system. Presented results show that low-cost smartphone IMU combined with PF can be applicable as proper navigation system.",
author = "Jussi Collin and Arto Perttula and Jussi Parviainen and Jan Racko and Peter Brida",
year = "2016",
month = "11",
day = "17",
doi = "10.1109/IPIN.2016.7743608",
language = "English",
publisher = "IEEE",
booktitle = "2016 International Conference on Indoor Positioning and Indoor Navigation (IPIN)",

}

RIS (suitable for import to EndNote) - Lataa

TY - GEN

T1 - Pedestrian Dead Reckoning with Particle Filter for Handheld Smartphone

AU - Collin, Jussi

AU - Perttula, Arto

AU - Parviainen, Jussi

AU - Racko, Jan

AU - Brida, Peter

PY - 2016/11/17

Y1 - 2016/11/17

N2 - Commonly used Global Navigation Satellite Systems (GNSS) are inappropriate as Location Based Services (LBS) in indoor environment. Therefore research teams are developing different systems, which can be used as a suitable alternative. One of options is to use Inertial Navigation System (INS) which consists of inertial sensors and mathematic procedures. This concept has been known for a long time, but with arrival of Microelectro Mechanical System (MEMS) INS found wide use. Smartphones with inertial sensors, such as accelerometers and gyroscopes, allow us to use them as input devices for Pedestrian Dead Reckoning (PDR). In this paper we present PDR by using smartphone sensors. They can be classified as low-cost Inertial Measurement Unit (IMU), and have been compared with more precise and expensive Xsens IMU. Accuracy of inertial sensors has increased in the past few years, but they still cannot alone provide proper accuracy because of many negative effects, such as heading drift due to gyroscope bias. Particle Filter (PF) has been successfully used with map constraints to increase the accuracy of proposed location system. Presented results show that low-cost smartphone IMU combined with PF can be applicable as proper navigation system.

AB - Commonly used Global Navigation Satellite Systems (GNSS) are inappropriate as Location Based Services (LBS) in indoor environment. Therefore research teams are developing different systems, which can be used as a suitable alternative. One of options is to use Inertial Navigation System (INS) which consists of inertial sensors and mathematic procedures. This concept has been known for a long time, but with arrival of Microelectro Mechanical System (MEMS) INS found wide use. Smartphones with inertial sensors, such as accelerometers and gyroscopes, allow us to use them as input devices for Pedestrian Dead Reckoning (PDR). In this paper we present PDR by using smartphone sensors. They can be classified as low-cost Inertial Measurement Unit (IMU), and have been compared with more precise and expensive Xsens IMU. Accuracy of inertial sensors has increased in the past few years, but they still cannot alone provide proper accuracy because of many negative effects, such as heading drift due to gyroscope bias. Particle Filter (PF) has been successfully used with map constraints to increase the accuracy of proposed location system. Presented results show that low-cost smartphone IMU combined with PF can be applicable as proper navigation system.

U2 - 10.1109/IPIN.2016.7743608

DO - 10.1109/IPIN.2016.7743608

M3 - Conference contribution

BT - 2016 International Conference on Indoor Positioning and Indoor Navigation (IPIN)

PB - IEEE

ER -