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Proceedings Paper

Pseudo K-means approach to the multisensor multitarget tracking problem
Author(s): Wiley E. Thompson; Ramon Parra; Chin-Wang Tao
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Paper Abstract

This paper presents a methodology for multitarget tracking based on multisensor data in a cluttered environment. Two very important problems of multitarget tracking are the clustering of multisensor measurements and data association. A clustering algorithm is presented which is based upon a pseudo k-means algorithm. This algorithm does not require a priori knowledge of the number of clusters expected and is computationally efficient in that no iterations are required. A data association technique is presented which does not require posteriori probabilities and utilizes only the basic augmented Kalman filter. Examples are presented to illustrate the effectiveness of the approach.

Paper Details

Date Published: 1 August 1991
PDF: 11 pages
Proc. SPIE 1470, Data Structures and Target Classification, (1 August 1991); doi: 10.1117/12.28803
Show Author Affiliations
Wiley E. Thompson, New Mexico State Univ. (United States)
Ramon Parra, New Mexico State Univ. (United States)
Chin-Wang Tao, New Mexico State Univ. (United States)


Published in SPIE Proceedings Vol. 1470:
Data Structures and Target Classification
Vibeke Libby, Editor(s)

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