NLOS error mitigation for TOA-based localization via convex relaxation

Gang Wang, H. Chen, Youming Li, Nirwan Ansari

Research output: Contribution to journalArticlepeer-review

157 Scopus citations


In this paper, we address the time-of-arrival (TOA) based localization problem in an adverse environment, where line-of-sight (LOS) signal propagation between the source and the sensor is not readily available, in which case we have to resort to non-line-of-sight (NLOS) signals. Two convex relaxation methods, i.e., the semidefinite relaxation (SDR) and the second-order cone relaxation (SOCR) methods, are proposed to mitigate the effect of NLOS errors on the localization performance. We consider two separate cases in which the information of the NLOS status is totally unknown and perfectly known, respectively. The proposed methods can be applied without knowing the distribution of NLOS errors. Moreover, we propose a NLOS error mitigation method that is robust to detection errors, which are generated in the process of detecting NLOS paths. Simulation results show that the proposed convex relaxation methods outperform some existing state-of-the-art methods.

Original languageEnglish (US)
Article number6781637
Pages (from-to)4119-4131
Number of pages13
JournalIEEE Transactions on Wireless Communications
Issue number8
StatePublished - Aug 2014

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics


  • Non-line-of-sight
  • Robust localization
  • Secondorder cone programming (SOCP)
  • Semidefinite programming
  • Time-of-arrival


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