Object tracking in 3-D space with passive acoustic sensors using particle filter

Jinseok Lee, Shung Han Cho, Sangjin Hong, Jaechan Lim, Seong Jun Oh

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


This paper considers the object tracking problem in three dimensional (3-D) space when the azimuth and elevation of the object are available from the passive acoustic sensor. The particle filtering technique can be directly applied to estimate the 3-D object location, but we propose to decompose the 3-D particle filter into the three planes' particle filters, which are individually designed for the 2-D bearings-only tracking problems. 2-D bearing information is derived from the azimuth and elevation of the object to be used for the 2-D particle filter. Two estimates of three planes' particle filters are selected based on the characterization of the acoustic sensor operation in a noisy environment. The Cramer-Rao Lower Bound of the proposed 2-D particle filter-based algorithm is derived and compared against the algorithm that is based on the direct 3-D particle filter.

Original languageEnglish
Pages (from-to)1632-1652
Number of pages21
JournalKSII Transactions on Internet and Information Systems
Issue number9
Publication statusPublished - 2011 Sept 29


  • 3-D object tracking
  • Acoustic sensors
  • Bearings-only tracking
  • Data fusion
  • Particle filter

ASJC Scopus subject areas

  • Information Systems
  • Computer Networks and Communications


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