Angelova, D and Mihaylova, L (2006) Joint target tracking and classification with particle filtering and mixture Kalman filtering using kinematic radar information. Digital Signal Processing, 16 (2). pp. 180-204. ISSN 1051-2004Full text not available from this repository.
This paper considers the problem of joint maneuvering target tracking and classification. Based on recently proposed Monte Carlo techniques, a multiple model (MM) particle filter and a mixture Kalman filter (MKF) are designed for two-class identification of air targets: commercial and military aircraft. The classification task is carried out by processing radar measurements only, no class (feature) measurements are used. A speed likelihood function for each class is defined using a prior information about speed constraints. Class-dependent speed likelihoods are calculated through the state estimates of each class-dependent tracker. They are combined with the kinematic measurement likelihoods in order to improve the classification process. The two designed estimators are compared and evaluated over rather complex target scenarios. The results demonstrate the usefulness of the proposed scheme for the incorporation of additional speed information. Both filters illustrate the opportunity of the particle filtering and mixture Kalman filtering to incorporate constraints in a natural way, providing reliable tracking and correct classification. Future observations contain valuable information about the current state of the dynamic systems. In the framework of the MKF, an algorithm for delayed estimation is designed for improving the current modal state estimate. It is used as an additional, more reliable information in resolving complicated classification situations.
|Journal or Publication Title:||Digital Signal Processing|
|Uncontrolled Keywords:||Joint tracking and classification ; Maneuvering target tracking ; DCS-publications-id ; art-753 ; DCS-publications-personnel-id ; 121|
|Departments:||Faculty of Science and Technology > School of Computing & Communications|
|Deposited By:||Dr L Mihaylov|
|Deposited On:||10 Dec 2007 08:46|
|Last Modified:||17 Jan 2017 01:52|
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