Hybrid RSS/AOA localization using approximated weighted least square in wireless sensor networks

Seyoung Kang, Taehyun Kim, Wonzoo Chung

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

We present a target localization method using an approximated error covariance matrix based weighted least squares (WLS) solution, which integrates received signal strength (RSS) and angle of arrival (AOA) data for wireless sensor networks. We approximated linear WLS errors via second-order Taylor approximation, and further approximated the error covariance matrix using a least-squares solution and the variance in measurement noise over the sensor nodes. The algorithm does not require any prior knowledge of the true target position or noise variance. Simulations validated the superior performance of our new method.

Original languageEnglish
Article number1159
JournalSensors (Switzerland)
Volume20
Issue number4
DOIs
Publication statusPublished - 2020 Feb 2

Keywords

  • Angle of arrival (AOA)
  • Received signal strength (RSS)
  • Target localization
  • Weighted least square (WLS)
  • Wireless sensor network (WSN)

ASJC Scopus subject areas

  • Analytical Chemistry
  • Biochemistry
  • Atomic and Molecular Physics, and Optics
  • Instrumentation
  • Electrical and Electronic Engineering

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