Consistency-based Air Target Height Estimation and Location in Distributed Space-based Radar Network
When single space-based radar tracks and detects air targets, problems such as missing pitch angle information and nonlinear measurement lead to large target height estimation errors. Multi-space-based radar networking can solve this problem. Moreover, considering the system’s requirements for low c...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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China Science Publishing & Media Ltd. (CSPM)
2023-12-01
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| Series: | Leida xuebao |
| Subjects: | |
| Online Access: | https://radars.ac.cn/cn/article/doi/10.12000/JR23157 |
| _version_ | 1797372423290486784 |
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| author | Zengfu WANG Yi SHAO Dengliang QI Shuling JIN |
| author_facet | Zengfu WANG Yi SHAO Dengliang QI Shuling JIN |
| author_sort | Zengfu WANG |
| collection | DOAJ |
| description | When single space-based radar tracks and detects air targets, problems such as missing pitch angle information and nonlinear measurement lead to large target height estimation errors. Multi-space-based radar networking can solve this problem. Moreover, considering the system’s requirements for low computational complexity, low communication overhead, high accuracy, and high reliability, a consistency-based method for height estimation and location of air targets in a distributed space-based radar network is proposed. First, an air target motion model and a space-based radar measurement model are presented. Second, based on probabilistic graphical model theory, a factor graph for multi-frame measurement of target tracking and positioning in a space-based radar network is established. The coupling relationship between several local target motion states is established based on consistency fusion. Third, combining particle filtering and belief propagation establishes the message representation and iterative calculation rules of nonparametric belief propagation on the fusion tracking for factor graph of space-based radar networking. Finally, the performance of the algorithm is tested through simulation. The simulation results show that compared with the distributed consensus extended Kalman filter, the proposed algorithm improves the target height estimation accuracy by 35.3%, effectively improving the target localization performance of the space-based radar. |
| first_indexed | 2024-03-08T18:35:34Z |
| format | Article |
| id | doaj.art-3e641abf247c4d2290ccc7e879514e58 |
| institution | Directory Open Access Journal |
| issn | 2095-283X |
| language | English |
| last_indexed | 2024-03-08T18:35:34Z |
| publishDate | 2023-12-01 |
| publisher | China Science Publishing & Media Ltd. (CSPM) |
| record_format | Article |
| series | Leida xuebao |
| spelling | doaj.art-3e641abf247c4d2290ccc7e879514e582023-12-29T12:27:27ZengChina Science Publishing & Media Ltd. (CSPM)Leida xuebao2095-283X2023-12-011261249126210.12000/JR23157R23157Consistency-based Air Target Height Estimation and Location in Distributed Space-based Radar NetworkZengfu WANG0Yi SHAO1Dengliang QI2Shuling JIN3School of Automation, Northwestern Polytechnical University, Xi’an 710072, ChinaXi’an Aerospace Propulsion Testing Technique Institute, Xi’an 710100, ChinaSchool of Automation, Northwestern Polytechnical University, Xi’an 710072, ChinaThe 38th Research Institute of China Electronics Technology Group Corporation, Hefei 230088, ChinaWhen single space-based radar tracks and detects air targets, problems such as missing pitch angle information and nonlinear measurement lead to large target height estimation errors. Multi-space-based radar networking can solve this problem. Moreover, considering the system’s requirements for low computational complexity, low communication overhead, high accuracy, and high reliability, a consistency-based method for height estimation and location of air targets in a distributed space-based radar network is proposed. First, an air target motion model and a space-based radar measurement model are presented. Second, based on probabilistic graphical model theory, a factor graph for multi-frame measurement of target tracking and positioning in a space-based radar network is established. The coupling relationship between several local target motion states is established based on consistency fusion. Third, combining particle filtering and belief propagation establishes the message representation and iterative calculation rules of nonparametric belief propagation on the fusion tracking for factor graph of space-based radar networking. Finally, the performance of the algorithm is tested through simulation. The simulation results show that compared with the distributed consensus extended Kalman filter, the proposed algorithm improves the target height estimation accuracy by 35.3%, effectively improving the target localization performance of the space-based radar.https://radars.ac.cn/cn/article/doi/10.12000/JR23157space-based radartarget trackingfactor graphnonparametric belief propagationkernel density estimation |
| spellingShingle | Zengfu WANG Yi SHAO Dengliang QI Shuling JIN Consistency-based Air Target Height Estimation and Location in Distributed Space-based Radar Network Leida xuebao space-based radar target tracking factor graph nonparametric belief propagation kernel density estimation |
| title | Consistency-based Air Target Height Estimation and Location in Distributed Space-based Radar Network |
| title_full | Consistency-based Air Target Height Estimation and Location in Distributed Space-based Radar Network |
| title_fullStr | Consistency-based Air Target Height Estimation and Location in Distributed Space-based Radar Network |
| title_full_unstemmed | Consistency-based Air Target Height Estimation and Location in Distributed Space-based Radar Network |
| title_short | Consistency-based Air Target Height Estimation and Location in Distributed Space-based Radar Network |
| title_sort | consistency based air target height estimation and location in distributed space based radar network |
| topic | space-based radar target tracking factor graph nonparametric belief propagation kernel density estimation |
| url | https://radars.ac.cn/cn/article/doi/10.12000/JR23157 |
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