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Content Provider | SpringerLink |
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Author | Yang, Jin Long Ji, Hong Bing Fan, Zhen Hua |
Copyright Year | 2013 |
Abstract | Taking into account the difficulties of multiple maneuvering target tracking due to the unknown target number and the uncertain acceleration, a novel multiple maneuvering target tracking algorithm based on the Probability Hypothesis Density (PHD) filter and Modified Input Estimation (MIE) technique is proposed in this paper. First, the unknown acceleration vector is added to the target state to form a new augmented state vector. Then, strong tracking filter multiple fading factors are introduced to the MIE method which can adjust the prediction covariance and the corresponding filter gain at different rates in real time, so that the MIE method can adaptively track high maneuvering targets well. Finally, we combine this adaptive MIE method with the PHD filter, which can effectively track multiple maneuvering targets without much prior information. Simulation results show that the proposed algorithm has a higher tracking precision and a better real-time performance than the conventional maneuvering target tracking algorithms. |
Starting Page | 306 |
Ending Page | 316 |
Page Count | 11 |
File Format | |
ISSN | 15986446 |
Journal | International Journal of Control, Automation and Systems |
Volume Number | 11 |
Issue Number | 2 |
e-ISSN | 20054092 |
Language | English |
Publisher | Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers |
Publisher Date | 2013-03-27 |
Publisher Place | Heidelberg |
Access Restriction | One Nation One Subscription (ONOS) |
Subject Keyword | Maneuvering target tracking modified input estimation multiple fading factors probability hypothesis density Control, Robotics, Mechatronics |
Content Type | Text |
Resource Type | Article |
Subject | Control and Systems Engineering Computer Science Applications |
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