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1 August 1991 Pseudo K-means approach to the multisensor multitarget tracking problem
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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.
© (1991) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Wiley E. Thompson, Ramon Parra, and Chin-Wang Tao "Pseudo K-means approach to the multisensor multitarget tracking problem", Proc. SPIE 1470, Data Structures and Target Classification, (1 August 1991); https://doi.org/10.1117/12.28803
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