Modified leaky LMS algorithms applied to satellite positioning

J. P. Montillet, Kegen Yu

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

6 Citations (Scopus)


With the recent advances in the theory of fractional Brownian motion (fBm), this model is used to describe the position coordinate estimates of Global Navigation Satellite System (GNSS) receivers that have long-range dependencies. The Modified Leaky Least Mean Squares (ML-LMS) algorithms are 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 using field measurements demonstrate that these proposed modified leaky least mean squares algorithms can outperform the classical LMS filter considerably in terms of accuracy (mean squared error) and convergence. We also deal with the case study where our proposed algorithms outperform the leaky LMS. The algorithms are tested on simulated and real measurements.

Original languageEnglish
Title of host publicationVTC2014-Fall
Subtitle of host publicationProceedings of the 2014 IEEE 80th Vehicular Technology Conference
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages5
ISBN (Electronic)9781479944491, 9781479944507
ISBN (Print)9781479944484
Publication statusPublished - 24 Nov 2014
Externally publishedYes
Event80th IEEE Vehicular Technology Conference, VTC 2014-Fall - Vancouver, Canada
Duration: 14 Sept 201417 Sept 2014


Other80th IEEE Vehicular Technology Conference, VTC 2014-Fall


  • fractional Brownian motion model
  • GNSS positioning
  • Hurst parameter
  • LMS
  • modified leaky LMS


Dive into the research topics of 'Modified leaky LMS algorithms applied to satellite positioning'. Together they form a unique fingerprint.

Cite this