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| Extended Target Tracking Method Based on Multi-Bernoulli Probability Hypothesis Density |
| LI Wenjuan GU Hong SU Weimin |
| (School of Electronic Engineering and Optoelectronic Technology, Nanjing University of Science and Technology, Nanjing 210094, China) |
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Abstract Extended targets usually generate multiple measurements in high resolution radar systems. Existing algorithms of the Random Finite Set (RFS) assume that the measurement number of extended targets follows Poisson distribution in a general way. However, this assumption is inconsistent with actual situations. Considering this issue, a Multi-Bernoulli Extended Target Probability Hypothesis Density (MB-ET-PHD) tracking method is proposed. First, this method assumes that the measurement number of extended targets is Multi-Bernoulli (MB) distributed. Then, its update equation is derived by using the FInite Set STatistics (FISST) multi-target calculus. Finally, simulated results of Gaussian Mixture (GM) framework are given. The simulation results show that the proposed method can obtain better tracking performance compared with the Poisson ET-PHD method.
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Received: 18 April 2016
Published: 21 October 2016
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| Fund: The National Natural Science Foundation of China (61471198) |
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Corresponding Authors:
GU Hong
E-mail: guhongjust@163.com
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