Leaky LMS algorithm and fractional Brownian motion model for GNSS receiver position estimation

Jean Philippe Montillet; Kegen Yu

doi:10.1109/VETECF.2011.6092850

Leaky LMS algorithm and fractional Brownian motion model for GNSS receiver position estimation

Jean Philippe Montillet^*, Kegen Yu

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

5 Citations (Scopus)

Abstract

This paper presents a new approach for smoothing long time series of position estimates of ground GNSS (global navigation satellite system) receivers. The fractional Brownian motion (fBm) model is employed to describe the position coordinate estimates that have long-range dependencies. A new and low-complexity method is proposed to estimate the Hurst parameter and the simulation results show that the new method achieves good accuracy and low complexity. A modified leaky least mean squares (ML-LMS) estimator is proposed to filter the long time series of the position coordinate estimates, which uses the Hurst parameter estimates to update the filter tap weights. Simulation results demonstrate that this ML-LMS estimator outperforms the classic LMS estimator considerably in terms of both accuracy and convergence.

Original language	English
Title of host publication	VTC Fall 2011
Subtitle of host publication	2011 IEEE Vehicular Technology Conference Fall
Place of Publication	Piscataway, NJ
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Number of pages	5
ISBN (Electronic)	9781424483273, 9781424483266
ISBN (Print)	9781424483280
DOIs	https://doi.org/10.1109/VETECF.2011.6092850
Publication status	Published - 2011
Externally published	Yes
Event	IEEE 74th Vehicular Technology Conference, VTC Fall 2011 - San Francisco, CA, United States Duration: 5 Sept 2011 → 8 Sept 2011

Other

Other	IEEE 74th Vehicular Technology Conference, VTC Fall 2011
Country/Territory	United States
City	San Francisco, CA
Period	5/09/11 → 8/09/11

Keywords

GNSS positioning
fractional Browinian motion model
Hurst parameter estimation
modified leaky LMS estimator

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10.1109/VETECF.2011.6092850

Cite this

@inproceedings{b2f77c34a06e44c4b05b6e7af9154bf7,

title = "Leaky LMS algorithm and fractional Brownian motion model for GNSS receiver position estimation",

abstract = "This paper presents a new approach for smoothing long time series of position estimates of ground GNSS (global navigation satellite system) receivers. The fractional Brownian motion (fBm) model is employed to describe the position coordinate estimates that have long-range dependencies. A new and low-complexity method is proposed to estimate the Hurst parameter and the simulation results show that the new method achieves good accuracy and low complexity. A modified leaky least mean squares (ML-LMS) estimator is proposed to filter the long time series of the position coordinate estimates, which uses the Hurst parameter estimates to update the filter tap weights. Simulation results demonstrate that this ML-LMS estimator outperforms the classic LMS estimator considerably in terms of both accuracy and convergence.",

keywords = "GNSS positioning, fractional Browinian motion model, Hurst parameter estimation, modified leaky LMS estimator",

author = "Montillet, {Jean Philippe} and Kegen Yu",

year = "2011",

doi = "10.1109/VETECF.2011.6092850",

language = "English",

isbn = "9781424483280",

booktitle = "VTC Fall 2011",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

address = "United States",

note = "IEEE 74th Vehicular Technology Conference, VTC Fall 2011 ; Conference date: 05-09-2011 Through 08-09-2011",

}

Montillet, JP & Yu, K 2011, Leaky LMS algorithm and fractional Brownian motion model for GNSS receiver position estimation. in VTC Fall 2011: 2011 IEEE Vehicular Technology Conference Fall. Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, IEEE 74th Vehicular Technology Conference, VTC Fall 2011, San Francisco, CA, United States, 5/09/11. https://doi.org/10.1109/VETECF.2011.6092850

Leaky LMS algorithm and fractional Brownian motion model for GNSS receiver position estimation. / Montillet, Jean Philippe; Yu, Kegen.
VTC Fall 2011: 2011 IEEE Vehicular Technology Conference Fall. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2011.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

TY - GEN

T1 - Leaky LMS algorithm and fractional Brownian motion model for GNSS receiver position estimation

AU - Montillet, Jean Philippe

AU - Yu, Kegen

PY - 2011

Y1 - 2011

N2 - This paper presents a new approach for smoothing long time series of position estimates of ground GNSS (global navigation satellite system) receivers. The fractional Brownian motion (fBm) model is employed to describe the position coordinate estimates that have long-range dependencies. A new and low-complexity method is proposed to estimate the Hurst parameter and the simulation results show that the new method achieves good accuracy and low complexity. A modified leaky least mean squares (ML-LMS) estimator is proposed to filter the long time series of the position coordinate estimates, which uses the Hurst parameter estimates to update the filter tap weights. Simulation results demonstrate that this ML-LMS estimator outperforms the classic LMS estimator considerably in terms of both accuracy and convergence.

AB - This paper presents a new approach for smoothing long time series of position estimates of ground GNSS (global navigation satellite system) receivers. The fractional Brownian motion (fBm) model is employed to describe the position coordinate estimates that have long-range dependencies. A new and low-complexity method is proposed to estimate the Hurst parameter and the simulation results show that the new method achieves good accuracy and low complexity. A modified leaky least mean squares (ML-LMS) estimator is proposed to filter the long time series of the position coordinate estimates, which uses the Hurst parameter estimates to update the filter tap weights. Simulation results demonstrate that this ML-LMS estimator outperforms the classic LMS estimator considerably in terms of both accuracy and convergence.

KW - GNSS positioning

KW - fractional Browinian motion model

KW - Hurst parameter estimation

KW - modified leaky LMS estimator

UR - http://www.scopus.com/inward/record.url?scp=83755163582&partnerID=8YFLogxK

U2 - 10.1109/VETECF.2011.6092850

DO - 10.1109/VETECF.2011.6092850

M3 - Conference proceeding contribution

AN - SCOPUS:83755163582

SN - 9781424483280

BT - VTC Fall 2011

PB - Institute of Electrical and Electronics Engineers (IEEE)

CY - Piscataway, NJ

T2 - IEEE 74th Vehicular Technology Conference, VTC Fall 2011

Y2 - 5 September 2011 through 8 September 2011

ER -

Leaky LMS algorithm and fractional Brownian motion model for GNSS receiver position estimation

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