Maneuvering Target Tracking Using Simultaneous Optimization and Feedback Learning Algorithm Based on Elman Neural Network
Tracking maneuvering targets is a challenging problem for sensors because of the unpredictability of the target’s motion. Unlike classical statistical modeling of target maneuvers, a simultaneous optimization and feedback learning algorithm for maneuvering target tracking based on the Elma...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-04-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/19/7/1596 |
| _version_ | 1817992000385843200 |
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| author | Huajun Liu Liwei Xia Cailing Wang |
| author_facet | Huajun Liu Liwei Xia Cailing Wang |
| author_sort | Huajun Liu |
| collection | DOAJ |
| description | Tracking maneuvering targets is a challenging problem for sensors because of the unpredictability of the target’s motion. Unlike classical statistical modeling of target maneuvers, a simultaneous optimization and feedback learning algorithm for maneuvering target tracking based on the Elman neural network (ENN) is proposed in this paper. In the feedback strategy, a scale factor is learnt to adaptively tune the dynamic model’s error covariance matrix, and in the optimization strategy, a corrected component of the state vector is learnt to refine the final state estimation. These two strategies are integrated in an ENN-based unscented Kalman filter (UKF) model called ELM-UKF. This filter can be trained online by the filter residual, innovation and gain matrix of the UKF to simultaneously achieve maneuver feedback and an optimized estimation. Monte Carlo experiments on synthesized radar data showed that our algorithm had better performance on filtering precision compared with most maneuvering target tracking algorithms. |
| first_indexed | 2024-04-14T01:20:52Z |
| format | Article |
| id | doaj.art-9665bc86dc584ddd9245d14f26938823 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-14T01:20:52Z |
| publishDate | 2019-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-9665bc86dc584ddd9245d14f269388232022-12-22T02:20:40ZengMDPI AGSensors1424-82202019-04-01197159610.3390/s19071596s19071596Maneuvering Target Tracking Using Simultaneous Optimization and Feedback Learning Algorithm Based on Elman Neural NetworkHuajun Liu0Liwei Xia1Cailing Wang2School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210014, ChinaSchool of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210014, ChinaRobotics Institute, Carnegie Mellon University, Pittsburgh, PA 15217, USATracking maneuvering targets is a challenging problem for sensors because of the unpredictability of the target’s motion. Unlike classical statistical modeling of target maneuvers, a simultaneous optimization and feedback learning algorithm for maneuvering target tracking based on the Elman neural network (ENN) is proposed in this paper. In the feedback strategy, a scale factor is learnt to adaptively tune the dynamic model’s error covariance matrix, and in the optimization strategy, a corrected component of the state vector is learnt to refine the final state estimation. These two strategies are integrated in an ENN-based unscented Kalman filter (UKF) model called ELM-UKF. This filter can be trained online by the filter residual, innovation and gain matrix of the UKF to simultaneously achieve maneuver feedback and an optimized estimation. Monte Carlo experiments on synthesized radar data showed that our algorithm had better performance on filtering precision compared with most maneuvering target tracking algorithms.https://www.mdpi.com/1424-8220/19/7/1596Elman neural networkmaneuvering target trackingsimultaneous optimization and feedback learning |
| spellingShingle | Huajun Liu Liwei Xia Cailing Wang Maneuvering Target Tracking Using Simultaneous Optimization and Feedback Learning Algorithm Based on Elman Neural Network Sensors Elman neural network maneuvering target tracking simultaneous optimization and feedback learning |
| title | Maneuvering Target Tracking Using Simultaneous Optimization and Feedback Learning Algorithm Based on Elman Neural Network |
| title_full | Maneuvering Target Tracking Using Simultaneous Optimization and Feedback Learning Algorithm Based on Elman Neural Network |
| title_fullStr | Maneuvering Target Tracking Using Simultaneous Optimization and Feedback Learning Algorithm Based on Elman Neural Network |
| title_full_unstemmed | Maneuvering Target Tracking Using Simultaneous Optimization and Feedback Learning Algorithm Based on Elman Neural Network |
| title_short | Maneuvering Target Tracking Using Simultaneous Optimization and Feedback Learning Algorithm Based on Elman Neural Network |
| title_sort | maneuvering target tracking using simultaneous optimization and feedback learning algorithm based on elman neural network |
| topic | Elman neural network maneuvering target tracking simultaneous optimization and feedback learning |
| url | https://www.mdpi.com/1424-8220/19/7/1596 |
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