Pseudo K-means approach to the multisensor multitarget tracking problem

Wiley E. Thompson; Ramon Parra; Chin-Wang Tao

doi:10.1117/12.28803

1 August 1991 Pseudo K-means approach to the multisensor multitarget tracking problem

Wiley E. Thompson, Ramon Parra, Chin-Wang Tao

Proceedings Volume 1470, Data Structures and Target Classification; (1991) https://doi.org/10.1117/12.28803
Event: Orlando '91, 1991, Orlando, FL, United States

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.

Citation Download Citation

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

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available