Efficient location estimators in NLOS environments

Kegen Yu*, Y. Jay Guo

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

2 Citations (Scopus)

Abstract

In the paper we consider location estimation in an non-line-of-sight (NLOS) environment. A constrained optimization based location algorithm is proposed to jointly estimate the unknown location and bias by using the sequential quadratic programming (SQP) algorithm. This method does not rely on any prior statistics information, and simulation results show that the proposed method outperforms the existing related methods considerably. To reduce the complexity of the SQP based algorithm, we further propose a Taylor-series expansion based linear quadratic programming (TS-LQP) algorithm. Simulation results demonstrate that the computational complexity of the TS-LQP algorithm is only a fraction of that of the SQP algorithm while the accuracy loss is marginal.

Original languageEnglish
Title of host publication18th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC'07
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1-5
Number of pages5
ISBN (Print)1424411440, 9781424411443
DOIs
Publication statusPublished - 2007
Externally publishedYes
Event18th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC'07 - Athens, Greece
Duration: 3 Sep 20077 Sep 2007

Other

Other18th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC'07
CountryGreece
CityAthens
Period3/09/077/09/07

Keywords

  • Constrained optimization
  • Joint location and bias estimation
  • NLOS propagation
  • Radio positioning

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