Multiaspect target detection via the infinite hidden Markov model.
Journal Article (Journal Article)
A new multiaspect target detection method is presented based on the infinite hidden Markov model (iHMM). The scattering of waves from a target is modeled as an iHMM with the number of underlying states treated as infinite, from which a full posterior distribution on the number of states associated with the targets is inferred and the target-dependent states are learned collectively. A set of Dirichlet processes (DPs) are used to define the rows of the HMM transition matrix and these DPs are linked and shared via a hierarchical Dirichlet process. Learning and inference for the iHMM are based on a Gibbs sampler. The basic framework is applied to a detailed analysis of measured acoustic scattering data.
Full Text
Duke Authors
Cited Authors
- Ni, K; Qi, Y; Carin, L
Published Date
- May 2007
Published In
Volume / Issue
- 121 / 5 Pt1
Start / End Page
- 2731 - 2742
PubMed ID
- 17550173
Electronic International Standard Serial Number (EISSN)
- 1520-8524
International Standard Serial Number (ISSN)
- 0001-4966
Digital Object Identifier (DOI)
- 10.1121/1.2714912
Language
- eng