Distributed Multi-Bernoulli Extended Targets Tracking Based on Arithmetic Average Fusion

WU Sunyong; ZHENG Xiangfei; LI Tiancheng; HU Qingshuang; LÜ Xiaoyan

doi:10.11999/JEIT220688

Volume 45 Issue 6

Jun. 2023

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Article Navigation > Journal of Electronics & Information Technology > 2023 > 45(6): 2171-2179

WU Sunyong, ZHENG Xiangfei, LI Tiancheng, HU Qingshuang, LÜ Xiaoyan. Distributed Multi-Bernoulli Extended Targets Tracking Based on Arithmetic Average Fusion[J]. Journal of Electronics & Information Technology, 2023, 45(6): 2171-2179. doi: 10.11999/JEIT220688

Citation:

WU Sunyong, ZHENG Xiangfei, LI Tiancheng, HU Qingshuang, LÜ Xiaoyan. Distributed Multi-Bernoulli Extended Targets Tracking Based on Arithmetic Average Fusion[J]. Journal of Electronics & Information Technology, 2023, 45(6): 2171-2179. doi: 10.11999/JEIT220688

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Distributed Multi-Bernoulli Extended Targets Tracking Based on Arithmetic Average Fusion

doi: 10.11999/JEIT220688

1.
Mathematics and Computer Science College of Guilin University of Electronic Technology, Guilin 541004, China
2.
Guangxi Key Laboratory of Cryptography and Information Security, Guilin 541004, China
3.
School of Automation, Northwestern Polytechnical University, Xi’an 710071, China

Funds: The National Natural Science Foundation of China (62263007,62061010, 62161007, 62071389), The Central Government Guided Local Science and Technology Development Fund Project (2022YZX2001), Guangxi Science and Technology Department Project (AA19182007), Guangxi Key Laboratory of Cryptography and Information Security (GCIS202132), The Graduate Innovation Program of School of Mathematics and Computing Science, GUET (2022YJSCX02), The Innovation Project of GUET Graduate Education (2022YCXS145)

Received Date: 2022-05-27
Rev Recd Date: 2022-09-03

Available Online: 2022-09-08

Publish Date: 2023-06-10

Abstract

Abstract

In distributed sensor networks, the inconsistent estimation results of state parameters such as azimuth and axis lengths of the same extended target under different sensors lead to the difficulty of extended target estimation association, which gives rise to challenges to the subsequent density information fusion. Compared with the point target posterior density information, the extended target posterior density contains both centroid state and shape information. Moreover, the Ellipse Distance (ED) is proposed based on the Euclidean distance of centroid and non-Euclidean size-shape metric of shape matrix. The ellipse distance considers both the centroid state and shape information of the extended target, and better realizes the posterior density correlation of the same extended target under different sensors. In addition, in this paper, the approximate Gamma Gaussian Inverse Wishart (GGIW) distribution of fusion space density is derived under the Arithmetic Average (AA) fusion rule, and the AA fusion of posterior information of the same extended target under different sensors is realized. Simulation results show that the proposed algorithm can effectively track multiple extended targets in distributed sensor networks.
- Distributed network,
- Extended target,
- Ellipse Distance (ED),
- Arithmetic Average(AA),
- Gamma Gaussian Inverse Wishart (GGIW) distribution

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References(24)

References

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