Joint detection and localization in sensor networks based on local decisions

Ruixin Niu, Pramod K. Varshney

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

38 Scopus citations

Abstract

A generalized likelihood ratio test (GLRT) based decision fusion method that uses quantized data from local sensors is proposed to jointly detect and localize a target in a wireless sensor field. The signal intensity is assumed to be inversely proportional to a power of the distance from the target. The GLRT, its corresponding maximum likelihood (ML) estimator, and the Cramér-Rao lower bound (CRLB) are derived. Simulation results show that this fusion rule has a significantly improved detection performance, compared with the counting rule (for hard local decisions) or the intuitive fusion rules based on the average of sensor data (for soft local decisions).

Original languageEnglish (US)
Title of host publicationConference Record of the 40th Asilomar Conference on Signals, Systems and Computers, ACSSC '06
Pages525-529
Number of pages5
DOIs
StatePublished - Dec 1 2006
Event40th Asilomar Conference on Signals, Systems, and Computers, ACSSC '06 - Pacific Grove, CA, United States
Duration: Oct 29 2006Nov 1 2006

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
ISSN (Print)1058-6393

Other

Other40th Asilomar Conference on Signals, Systems, and Computers, ACSSC '06
CountryUnited States
CityPacific Grove, CA
Period10/29/0611/1/06

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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  • Cite this

    Niu, R., & Varshney, P. K. (2006). Joint detection and localization in sensor networks based on local decisions. In Conference Record of the 40th Asilomar Conference on Signals, Systems and Computers, ACSSC '06 (pp. 525-529). [4176613] (Conference Record - Asilomar Conference on Signals, Systems and Computers). https://doi.org/10.1109/ACSSC.2006.354803