Hybrid Fingerprinting and Ray Extension Localization in NLOS Regions

Jun Li, I. Tai Lu, Jonathan S. Lu

Research output: Contribution to journalArticlepeer-review


A general non-asymptotic theoretical analysis is developed for fingerprinting localization system designs. Based on this analysis, hybrid fingerprinting and propagation-based methods are proposed using 5G-like received signal strength (RSS), time of arrival (TOA), and direction of arrival (DOA) measurements which have been a focus in recent 3GPP Rel 16 and Rel 17 positioning activities. The proposed hybrid methods have the flexibility and robustness of fingerprinting methods in dealing with none-line-of-sight (NLOS) problem while inheriting the efficiency and accuracy of propagation-based methods in 3-D localization. Specifically, a ray extension technique is developed as the propagation-based method. Then the ray extension is combined with two fingerprinting methods, the conventional weighted k-nearest neighbors (WKNN) and the proposed optimal WKNN (OWKNN), in order to remedy the geometrical deficiency in fingerprinting methods. Based on the non-asymptotic study, the proposed hybrid methods are guaranteed to outperform the fingerprinting methods without ray extension. Verification of the proposed methods is performed in a large none-line-of-sight (NLOS) urban San Jose region using simulation data provided by a previously developed super-efficient ray launcher.

Original languageEnglish (US)
Pages (from-to)23503-23516
Number of pages14
JournalIEEE Transactions on Intelligent Transportation Systems
Issue number12
StatePublished - Dec 1 2022


  • 3GPP
  • 5G
  • DOA
  • NLOS
  • Positioning
  • RSS
  • TOA
  • WKNN
  • WSN
  • fingerprinting
  • wave propagation

ASJC Scopus subject areas

  • Mechanical Engineering
  • Automotive Engineering
  • Computer Science Applications


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