YUAN Changshun, WANG Jun, LEI Peng, SUN Jinping. Adaptive Multi-Bernoulli Filter Without Need of Prior Birth Multi-Bernoulli Random Finite Set[J]. Chinese Journal of Electronics, 2018, 27(1): 115-122. doi: 10.1049/cje.2017.10.010
Citation: YUAN Changshun, WANG Jun, LEI Peng, SUN Jinping. Adaptive Multi-Bernoulli Filter Without Need of Prior Birth Multi-Bernoulli Random Finite Set[J]. Chinese Journal of Electronics, 2018, 27(1): 115-122. doi: 10.1049/cje.2017.10.010

Adaptive Multi-Bernoulli Filter Without Need of Prior Birth Multi-Bernoulli Random Finite Set

doi: 10.1049/cje.2017.10.010
Funds:  This work is supported by the National Natural Science Foundation of China (No.61471019, No.61501011, No.61501012).
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  • Corresponding author: WANG Jun (corresponding author) received the B.S. degree from the Northwestern Polytechnical University, Xi'an, China, in 1995 and the M.S. and Ph.D. degrees from the Beihang University, Beijing, China, in 1998 and 2001, respectively. He is currently a professor with the School of Electronic and Information Engineering, Beihang University. His research interests signal processing, DSP/FPGA realtime architecture, target recognition and tracking, etc. (Email:wangj203@buaa.edu.cn)
  • Received Date: 2015-10-22
  • Rev Recd Date: 2016-05-19
  • Publish Date: 2018-01-10
  • Conventional Multi-Bernoulli (MBer) filter assumes that the birth MBer Random finite set (RFS) is known a priori. However, this is not true for practical scenario. This paper proposes a novel extension of the MBer filter which eliminates the reliance of the prior birth MBer RFS and relaxes the limitation in new-born target appearance volume. The proposed filter classifies the measurements into survival measurements and birth measurements, and adaptively generates the birth MBer RFS using the birth measurements. The novel filtering equations that distinguish the persistent and new-born targets are derived. A Sequential Monte-Carlo (SMC) implementation of the proposed filter is given. Simulations are performed to verify the improvement in the performance of the proposed filter.
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