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Mobile tracking in unknown non-line-of-sight conditions

Tutkimustuotos

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Mobile tracking in unknown non-line-of-sight conditions. / Liang, Chen; Pesonen, Henri; Piche, Robert.

Proceedings of the International Conference on Ubiquitous Positioning, Indoor Navigation and Location-Based Service UPINLBS 2010, October 14-15, 2010, Kirkkonummi, Finland. Helsinki, 2010. s. 1-4.

Tutkimustuotos

Harvard

Liang, C, Pesonen, H & Piche, R 2010, Mobile tracking in unknown non-line-of-sight conditions. julkaisussa Proceedings of the International Conference on Ubiquitous Positioning, Indoor Navigation and Location-Based Service UPINLBS 2010, October 14-15, 2010, Kirkkonummi, Finland. Helsinki, Sivut 1-4. https://doi.org/10.1109/UPINLBS.2010.5654324

APA

Liang, C., Pesonen, H., & Piche, R. (2010). Mobile tracking in unknown non-line-of-sight conditions. teoksessa Proceedings of the International Conference on Ubiquitous Positioning, Indoor Navigation and Location-Based Service UPINLBS 2010, October 14-15, 2010, Kirkkonummi, Finland (Sivut 1-4). Helsinki. https://doi.org/10.1109/UPINLBS.2010.5654324

Vancouver

Liang C, Pesonen H, Piche R. Mobile tracking in unknown non-line-of-sight conditions. julkaisussa Proceedings of the International Conference on Ubiquitous Positioning, Indoor Navigation and Location-Based Service UPINLBS 2010, October 14-15, 2010, Kirkkonummi, Finland. Helsinki. 2010. s. 1-4 https://doi.org/10.1109/UPINLBS.2010.5654324

Author

Liang, Chen ; Pesonen, Henri ; Piche, Robert. / Mobile tracking in unknown non-line-of-sight conditions. Proceedings of the International Conference on Ubiquitous Positioning, Indoor Navigation and Location-Based Service UPINLBS 2010, October 14-15, 2010, Kirkkonummi, Finland. Helsinki, 2010. Sivut 1-4

Bibtex - Lataa

@inproceedings{3c1fc8ff0d364bf6ab54e08a41c24bac,
title = "Mobile tracking in unknown non-line-of-sight conditions",
abstract = "This paper studies the mobile tracking problem in mixed line-of-sight (LOS) and non-line-of-sight (NLOS) conditions, where the statistics of NLOS error are assumed unknown. Three different models are used to describe the NLOS errors. A Rao-Blackwellized particle filtering with parameter learning (RBPF-PL) is presented, in which the posterior of sight conditions is estimated by particle filtering while the mobile state and NLOS parameters are analytically computed. Simulation results are provided to evaluate the performance of RBPF-PL variants in different situations. Simulation show that unless it is known that NLOS noise has the same bias and variance in all the observations, the more complicated models should be employed as they work correctly even in NLOS model mismatch, with only slightly more computational complexity.",
author = "Chen Liang and Henri Pesonen and Robert Piche",
note = "Contribution: organisation=mat,FACT1=1",
year = "2010",
doi = "10.1109/UPINLBS.2010.5654324",
language = "English",
isbn = "978-1-4244-7879-8",
pages = "1--4",
booktitle = "Proceedings of the International Conference on Ubiquitous Positioning, Indoor Navigation and Location-Based Service UPINLBS 2010, October 14-15, 2010, Kirkkonummi, Finland",

}

RIS (suitable for import to EndNote) - Lataa

TY - GEN

T1 - Mobile tracking in unknown non-line-of-sight conditions

AU - Liang, Chen

AU - Pesonen, Henri

AU - Piche, Robert

N1 - Contribution: organisation=mat,FACT1=1

PY - 2010

Y1 - 2010

N2 - This paper studies the mobile tracking problem in mixed line-of-sight (LOS) and non-line-of-sight (NLOS) conditions, where the statistics of NLOS error are assumed unknown. Three different models are used to describe the NLOS errors. A Rao-Blackwellized particle filtering with parameter learning (RBPF-PL) is presented, in which the posterior of sight conditions is estimated by particle filtering while the mobile state and NLOS parameters are analytically computed. Simulation results are provided to evaluate the performance of RBPF-PL variants in different situations. Simulation show that unless it is known that NLOS noise has the same bias and variance in all the observations, the more complicated models should be employed as they work correctly even in NLOS model mismatch, with only slightly more computational complexity.

AB - This paper studies the mobile tracking problem in mixed line-of-sight (LOS) and non-line-of-sight (NLOS) conditions, where the statistics of NLOS error are assumed unknown. Three different models are used to describe the NLOS errors. A Rao-Blackwellized particle filtering with parameter learning (RBPF-PL) is presented, in which the posterior of sight conditions is estimated by particle filtering while the mobile state and NLOS parameters are analytically computed. Simulation results are provided to evaluate the performance of RBPF-PL variants in different situations. Simulation show that unless it is known that NLOS noise has the same bias and variance in all the observations, the more complicated models should be employed as they work correctly even in NLOS model mismatch, with only slightly more computational complexity.

U2 - 10.1109/UPINLBS.2010.5654324

DO - 10.1109/UPINLBS.2010.5654324

M3 - Conference contribution

SN - 978-1-4244-7879-8

SP - 1

EP - 4

BT - Proceedings of the International Conference on Ubiquitous Positioning, Indoor Navigation and Location-Based Service UPINLBS 2010, October 14-15, 2010, Kirkkonummi, Finland

CY - Helsinki

ER -