Multitarget Tracking Using Distributed Radar with Partially Overlapping Fields of Views
The Fields of Views (FoVs) of radars in a distributed network partially overlap due to detecting capability, waveform design, and antenna orientation constraints, resulting in observed discrepancies between radars and a significant obstacle to future information fusion. In this paper, we propose a d...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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China Science Publishing & Media Ltd. (CSPM)
2022-06-01
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| Series: | Leida xuebao |
| Subjects: | |
| Online Access: | https://radars.ac.cn/cn/article/doi/10.12000/JR21183 |
| _version_ | 1797428193062289408 |
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| author | Kai DA Ye YANG Yongfeng ZHU Qiang FU |
| author_facet | Kai DA Ye YANG Yongfeng ZHU Qiang FU |
| author_sort | Kai DA |
| collection | DOAJ |
| description | The Fields of Views (FoVs) of radars in a distributed network partially overlap due to detecting capability, waveform design, and antenna orientation constraints, resulting in observed discrepancies between radars and a significant obstacle to future information fusion. In this paper, we propose a distributed multitarget tracking method under the scene of partially overlapping radar FoVs, based on the Gaussian Mixture Cardinalized Probability Hypothesis Density (GM-CPHD) filter. First, we employ the product of the multitarget densities to split the PHD functions and find the part that characterizes the information of the targets commonly observed by multiple radars. Then, a standard distributed fusion (arithmetic average or geometric average fusion) acts on the splitting information to improve tracking performance, and a compensation fusion acts on the remaining information to expand the observation FoV. The proposed method does not require prior knowledge of the radar’s FoV and may adapt to the scene of distributed multitarget tracking while the FoVs are unknown. Simulations are provided to verify the effectiveness of the proposed approach under the scene of unknown and time-varying radar FoVs, and show that the proposed method has better performance than that of the cluster method based on Gaussian matching. |
| first_indexed | 2024-03-09T08:55:29Z |
| format | Article |
| id | doaj.art-c2c5538e020a4160951f2550f9c0052c |
| institution | Directory Open Access Journal |
| issn | 2095-283X |
| language | English |
| last_indexed | 2024-03-09T08:55:29Z |
| publishDate | 2022-06-01 |
| publisher | China Science Publishing & Media Ltd. (CSPM) |
| record_format | Article |
| series | Leida xuebao |
| spelling | doaj.art-c2c5538e020a4160951f2550f9c0052c2023-12-02T13:20:28ZengChina Science Publishing & Media Ltd. (CSPM)Leida xuebao2095-283X2022-06-0111345946810.12000/JR21183R21183Multitarget Tracking Using Distributed Radar with Partially Overlapping Fields of ViewsKai DA0Ye YANG1Yongfeng ZHU2Qiang FU3National Key Laboratory of Science and Technology on ATR, College of Electronic Science and technology, National University of Defense Technology, Changsha 410073, ChinaNational Key Laboratory of Science and Technology on ATR, College of Electronic Science and technology, National University of Defense Technology, Changsha 410073, ChinaNational Key Laboratory of Science and Technology on ATR, College of Electronic Science and technology, National University of Defense Technology, Changsha 410073, ChinaNational Key Laboratory of Science and Technology on ATR, College of Electronic Science and technology, National University of Defense Technology, Changsha 410073, ChinaThe Fields of Views (FoVs) of radars in a distributed network partially overlap due to detecting capability, waveform design, and antenna orientation constraints, resulting in observed discrepancies between radars and a significant obstacle to future information fusion. In this paper, we propose a distributed multitarget tracking method under the scene of partially overlapping radar FoVs, based on the Gaussian Mixture Cardinalized Probability Hypothesis Density (GM-CPHD) filter. First, we employ the product of the multitarget densities to split the PHD functions and find the part that characterizes the information of the targets commonly observed by multiple radars. Then, a standard distributed fusion (arithmetic average or geometric average fusion) acts on the splitting information to improve tracking performance, and a compensation fusion acts on the remaining information to expand the observation FoV. The proposed method does not require prior knowledge of the radar’s FoV and may adapt to the scene of distributed multitarget tracking while the FoVs are unknown. Simulations are provided to verify the effectiveness of the proposed approach under the scene of unknown and time-varying radar FoVs, and show that the proposed method has better performance than that of the cluster method based on Gaussian matching.https://radars.ac.cn/cn/article/doi/10.12000/JR21183multisensor fusionrandom finite setdistributed radarmultitarget trackingpartially overlapping filed of view |
| spellingShingle | Kai DA Ye YANG Yongfeng ZHU Qiang FU Multitarget Tracking Using Distributed Radar with Partially Overlapping Fields of Views Leida xuebao multisensor fusion random finite set distributed radar multitarget tracking partially overlapping filed of view |
| title | Multitarget Tracking Using Distributed Radar with Partially Overlapping Fields of Views |
| title_full | Multitarget Tracking Using Distributed Radar with Partially Overlapping Fields of Views |
| title_fullStr | Multitarget Tracking Using Distributed Radar with Partially Overlapping Fields of Views |
| title_full_unstemmed | Multitarget Tracking Using Distributed Radar with Partially Overlapping Fields of Views |
| title_short | Multitarget Tracking Using Distributed Radar with Partially Overlapping Fields of Views |
| title_sort | multitarget tracking using distributed radar with partially overlapping fields of views |
| topic | multisensor fusion random finite set distributed radar multitarget tracking partially overlapping filed of view |
| url | https://radars.ac.cn/cn/article/doi/10.12000/JR21183 |
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