A novel track-before-detect algorithm based on optimal nonlinear filtering for detecting and tracking infrared dim target

Yuexin Tian, Kun Gao, Ying Liu, Lu Han

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

Aiming at the nonlinear and non-Gaussian features of the real infrared scenes, an optimal nonlinear filtering based algorithm for the infrared dim target tracking-before-detecting application is proposed. It uses the nonlinear theory to construct the state and observation models and uses the spectral separation scheme based Wiener chaos expansion method to resolve the stochastic differential equation of the constructed models. In order to improve computation efficiency, the most time-consuming operations independent of observation data are processed on the fore observation stage. The other observation data related rapid computations are implemented subsequently. Simulation results show that the algorithm possesses excellent detection performance and is more suitable for real-time processing.

Original languageEnglish
Title of host publication2015 International Conference on Optical Instruments and Technology
Subtitle of host publicationOptoelectronic Imaging and Processing Technology, OIT 2015
EditorsGuangming Shi, Bormin Huang, Xuelong Li
PublisherSPIE
ISBN (Electronic)9781628418033
DOIs
Publication statusPublished - 2015
Event2015 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology, OIT 2015 - Beijing, China
Duration: 17 May 201519 May 2015

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume9622
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference2015 International Conference on Optical Instruments and Technology: Optoelectronic Imaging and Processing Technology, OIT 2015
Country/TerritoryChina
CityBeijing
Period17/05/1519/05/15

Keywords

  • optimal nonlinear filtering
  • spectral separation scheme
  • track-before-detect
  • wiener chaos decomposition

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