Pseudo K-means approach to the multisensor multitarget tracking problem
Wiley E. Thompson, Ramon Parra, Chin‐Wang Tao · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1991
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.