Adaptive Data Fusion Method of Multisensors Based on LSTM-GWFA Hybrid Model for Tracking Dynamic Targets
In preparation for the battlefields of the future, using unmanned aerial vehicles (UAV) loaded with multisensors to track dynamic targets has become the research focus in recent years. According to the air combat tracking scenarios and traditional multisensor weighted fusion algorithms, this paper c...
| Main Authors: | , , , |
|---|---|
| 格式: | 文件 |
| 语言: | English |
| 出版: |
MDPI AG
2022-08-01
|
| 丛编: | Sensors |
| 主题: | |
| 在线阅读: | https://www.mdpi.com/1424-8220/22/15/5800 |
| _version_ | 1827618276897718272 |
|---|---|
| author | Hao Yin Dongguang Li Yue Wang Xiaotong Hong |
| author_facet | Hao Yin Dongguang Li Yue Wang Xiaotong Hong |
| author_sort | Hao Yin |
| collection | DOAJ |
| description | In preparation for the battlefields of the future, using unmanned aerial vehicles (UAV) loaded with multisensors to track dynamic targets has become the research focus in recent years. According to the air combat tracking scenarios and traditional multisensor weighted fusion algorithms, this paper contains designs of a new data fusion method using a global Kalman filter and LSTM prediction measurement variance, which uses an adaptive truncation mechanism to determine the optimal weights. The method considers the temporal correlation of the measured data and introduces a detection mechanism for maneuvering of targets. Numerical simulation results show the accuracy of the algorithm can be improved about 66% by training 871 flight data. Based on a mature refitted civil wing UAV platform, the field experiments verified the data fusion method for tracking dynamic target is effective, stable, and has generalization ability. |
| first_indexed | 2024-03-09T10:05:21Z |
| format | Article |
| id | doaj.art-489a1a4c852f434c8b92d91880bc63c5 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T10:05:21Z |
| publishDate | 2022-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-489a1a4c852f434c8b92d91880bc63c52023-12-01T23:10:28ZengMDPI AGSensors1424-82202022-08-012215580010.3390/s22155800Adaptive Data Fusion Method of Multisensors Based on LSTM-GWFA Hybrid Model for Tracking Dynamic TargetsHao Yin0Dongguang Li1Yue Wang2Xiaotong Hong3School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, ChinaSchool of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, ChinaSchool of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, ChinaSchool of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, ChinaIn preparation for the battlefields of the future, using unmanned aerial vehicles (UAV) loaded with multisensors to track dynamic targets has become the research focus in recent years. According to the air combat tracking scenarios and traditional multisensor weighted fusion algorithms, this paper contains designs of a new data fusion method using a global Kalman filter and LSTM prediction measurement variance, which uses an adaptive truncation mechanism to determine the optimal weights. The method considers the temporal correlation of the measured data and introduces a detection mechanism for maneuvering of targets. Numerical simulation results show the accuracy of the algorithm can be improved about 66% by training 871 flight data. Based on a mature refitted civil wing UAV platform, the field experiments verified the data fusion method for tracking dynamic target is effective, stable, and has generalization ability.https://www.mdpi.com/1424-8220/22/15/5800multisensordata fusionLSTMdynamic target tracking |
| spellingShingle | Hao Yin Dongguang Li Yue Wang Xiaotong Hong Adaptive Data Fusion Method of Multisensors Based on LSTM-GWFA Hybrid Model for Tracking Dynamic Targets Sensors multisensor data fusion LSTM dynamic target tracking |
| title | Adaptive Data Fusion Method of Multisensors Based on LSTM-GWFA Hybrid Model for Tracking Dynamic Targets |
| title_full | Adaptive Data Fusion Method of Multisensors Based on LSTM-GWFA Hybrid Model for Tracking Dynamic Targets |
| title_fullStr | Adaptive Data Fusion Method of Multisensors Based on LSTM-GWFA Hybrid Model for Tracking Dynamic Targets |
| title_full_unstemmed | Adaptive Data Fusion Method of Multisensors Based on LSTM-GWFA Hybrid Model for Tracking Dynamic Targets |
| title_short | Adaptive Data Fusion Method of Multisensors Based on LSTM-GWFA Hybrid Model for Tracking Dynamic Targets |
| title_sort | adaptive data fusion method of multisensors based on lstm gwfa hybrid model for tracking dynamic targets |
| topic | multisensor data fusion LSTM dynamic target tracking |
| url | https://www.mdpi.com/1424-8220/22/15/5800 |
| work_keys_str_mv | AT haoyin adaptivedatafusionmethodofmultisensorsbasedonlstmgwfahybridmodelfortrackingdynamictargets AT dongguangli adaptivedatafusionmethodofmultisensorsbasedonlstmgwfahybridmodelfortrackingdynamictargets AT yuewang adaptivedatafusionmethodofmultisensorsbasedonlstmgwfahybridmodelfortrackingdynamictargets AT xiaotonghong adaptivedatafusionmethodofmultisensorsbasedonlstmgwfahybridmodelfortrackingdynamictargets |