17. NLOS Mitigation Methods for Geolocation

  1. Seyed A. (Reza) Zekavat4 and
  2. R. Michael Buehrer5
  1. Joni Polili Lie1,
  2. Chin-Heng Lim2 and
  3. Chong-Meng Samson See2,3

Published Online: 6 SEP 2011

DOI: 10.1002/9781118104750.ch17

Handbook of Position Location: Theory, Practice, and Advances

Handbook of Position Location: Theory, Practice, and Advances

How to Cite

Lie, J. P., Lim, C.-H. and Samson See, C.-M. (2011) NLOS Mitigation Methods for Geolocation, in Handbook of Position Location: Theory, Practice, and Advances (eds S. A. (. Zekavat and R. M. Buehrer), John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9781118104750.ch17

Editor Information

  1. 4

    Michigan Technological University, Houghton, MI, USA

  2. 5

    Virginia Tech, Blacksburg, VA, USA

Author Information

  1. 1

    Temasek Laboratories, Nanyang Technological University, Singapore

  2. 2

    Nanyang Technological University, Singapore

  3. 3

    DSO National Laboratories, Singapore

Publication History

  1. Published Online: 6 SEP 2011
  2. Published Print: 16 SEP 2011

ISBN Information

Print ISBN: 9780470943427

Online ISBN: 9781118104750



  • constrained optimization techniques;
  • geolocation;
  • least squares (LS)-based techniques;
  • maximum likelihood (ML)-based techniques;
  • non-line-of-sight (NLOS) mitigation methods;
  • robust estimator techniques


The problem of locating mobile sensors has received considerable attention, particularly in the field of wireless communications. It is well known that the presence of non-line-of-sight (NLOS) errors in the geolocation problem leads to severe degradation in the localization performance. This chapter introduces NLOS mitigation methods for geolocation. Generally, the NLOS mitigation methods for geolocation can be grouped into four categories: maximum likelihood (ML)-based techniques, least squares (LS)-based techniques, constrained optimization techniques and robust estimator techniques. The chapter discusses these methods, and then compares these methods in terms of different performance measures. It also discusses a novel geolocation example using a single moving sensor. The chapter then presents numerical examples to demonstrate how position estimation can be achieved for the case of a single moving sensor with NLOS errors.

Controlled Vocabulary Terms

error correction; least squares approximations; maximum likelihood estimation; optimisation; position measurement