Conditional Rician K-Factor Discrimination for Indoor Localization via AOA Estimation

Donald L. Hall, David M. Jenkins

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


This paper proposes conditioning angle of arrival (AOA) algorithms for pseudo-spectrum fingerprint acquisition based on line of sight (LOS) and non-LOS detection schema for optimizing indoor localization. The proposed approach merges two AOA based methods being that of the MUltiple Signal Classsification (MUSIC) algorithm and virtual MUSIC algorithm into a conditional based localization approach with a uniform circular array (UCA). The paper begins by demonstrating the environmental dependencies of the two AOA approaches based on the Rician K-factor metric. The K-factor is then exploited as an algorithm selection metric to arrive at improved localization performance in a realistic indoor environment.

Original languageEnglish (US)
Title of host publicationMILCOM 2021 - 2021 IEEE Military Communications Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781665439565
StatePublished - 2021
Event2021 IEEE Military Communications Conference, MILCOM 2021 - San Diego, United States
Duration: Nov 29 2021Dec 2 2021

Publication series

NameProceedings - IEEE Military Communications Conference MILCOM


Conference2021 IEEE Military Communications Conference, MILCOM 2021
Country/TerritoryUnited States
CitySan Diego

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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