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- Title
Object Tracking in 3-D Space with Passive Acoustic Sensors using Particle Filter.
- Authors
Lee, Jinseok; Cho, Shung Han; Hong, Sangjin; Lim, Jaechan; Oh, Seong-Jun
- Abstract
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.
- Subjects
MULTISENSOR data fusion; THREE-dimensional imaging; ACOUSTICAL engineering; MONTE Carlo method; SIGNAL processing; ELECTRIC filters; COMPUTER engineering; DETECTORS
- Publication
KSII Transactions on Internet & Information Systems, 2011, Vol 5, Issue 9, p1632
- ISSN
1976-7277
- Publication type
Article
- DOI
10.3837/tiis.2011.09.008