Mixture reduction techniques and probabilistic intensity models for multiple hypothesis tracking of targets in clutter

Author:

Kennedy Hugh L.

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,General Computer Science,Control and Systems Engineering

Reference33 articles.

1. Multiple hypothesis tracking for multiple target tracking;Blackman;IEEE Aerosp Electron Syst Mag,2004

2. Infrared small target enhancement and detection based on modified top-hat transformations;Bai;Comput Elec Eng,2010

3. Small target detection using cross product based on temporal profile in infrared image sequences;Bae;Comput Electr Eng,2010

4. Crouse DF, Willett P, Pattipati K, Svensson L. A look at Gaussian mixture reduction algorithms. In: Proc 14th int conf on information fusion; 2011. p. 1–8.

5. Probabilistic data association techniques for target tracking with applications to sonar, radar and EO sensors;Bar-Shalom;IEEE Aerosp Electr Syst Mag,2005

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