Optimal Configuration Analysis of AOA Localization and Optimal Heading Angles Generation Method for UAV Swarms
In this paper, the angle-of-arrival (AOA) measurements are adapted to locate a target using the UAV swarms equipped with passive receivers. The measurement noise is considered to be target-to-receiver distance dependent. The Cramer-Rao low bound (CRLB) of the AOA localization is calculated, and the...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2019-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8720270/ |
| _version_ | 1818728073163440128 |
|---|---|
| author | Weijia Wang Peng Bai Yu Zhou Xiaolong Liang Yubing Wang |
| author_facet | Weijia Wang Peng Bai Yu Zhou Xiaolong Liang Yubing Wang |
| author_sort | Weijia Wang |
| collection | DOAJ |
| description | In this paper, the angle-of-arrival (AOA) measurements are adapted to locate a target using the UAV swarms equipped with passive receivers. The measurement noise is considered to be target-to-receiver distance dependent. The Cramer-Rao low bound (CRLB) of the AOA localization is calculated, and the optimal deployments are explored through changing angular separations and distances. Then, a distributed collaborative autonomous generation (DCAG) method is proposed based on the deep neural network (NN). The off-line training and on-line application rules are applied to generate the optimal heading angles for the UAV swarms in the AOA localization. The simulation results show that through the DCAG method, the generated heading angles for UAV swarms enhance the localization accuracy and stability. |
| first_indexed | 2024-12-17T22:24:11Z |
| format | Article |
| id | doaj.art-300d2ad4da714f89b2ab985be6bc0807 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-17T22:24:11Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-300d2ad4da714f89b2ab985be6bc08072022-12-21T21:30:23ZengIEEEIEEE Access2169-35362019-01-017701177012910.1109/ACCESS.2019.29182998720270Optimal Configuration Analysis of AOA Localization and Optimal Heading Angles Generation Method for UAV SwarmsWeijia Wang0https://orcid.org/0000-0001-9643-6703Peng Bai1Yu Zhou2Xiaolong Liang3Yubing Wang4https://orcid.org/0000-0002-6179-9384Air Traffic Control and Navigation College, Air Force Engineering University, Xi’an, ChinaAir Traffic Control and Navigation College, Air Force Engineering University, Xi’an, ChinaEquipment Management & UAV Engineering College, Air Force Engineering University, Xi’an, ChinaAir Traffic Control and Navigation College, Air Force Engineering University, Xi’an, ChinaAir Traffic Control and Navigation College, Air Force Engineering University, Xi’an, ChinaIn this paper, the angle-of-arrival (AOA) measurements are adapted to locate a target using the UAV swarms equipped with passive receivers. The measurement noise is considered to be target-to-receiver distance dependent. The Cramer-Rao low bound (CRLB) of the AOA localization is calculated, and the optimal deployments are explored through changing angular separations and distances. Then, a distributed collaborative autonomous generation (DCAG) method is proposed based on the deep neural network (NN). The off-line training and on-line application rules are applied to generate the optimal heading angles for the UAV swarms in the AOA localization. The simulation results show that through the DCAG method, the generated heading angles for UAV swarms enhance the localization accuracy and stability.https://ieeexplore.ieee.org/document/8720270/AOA localizationdistributed collaborative autonomous generation (DCAG)Cramer-Rao low bound (CRLB)deep neural network (NN) |
| spellingShingle | Weijia Wang Peng Bai Yu Zhou Xiaolong Liang Yubing Wang Optimal Configuration Analysis of AOA Localization and Optimal Heading Angles Generation Method for UAV Swarms IEEE Access AOA localization distributed collaborative autonomous generation (DCAG) Cramer-Rao low bound (CRLB) deep neural network (NN) |
| title | Optimal Configuration Analysis of AOA Localization and Optimal Heading Angles Generation Method for UAV Swarms |
| title_full | Optimal Configuration Analysis of AOA Localization and Optimal Heading Angles Generation Method for UAV Swarms |
| title_fullStr | Optimal Configuration Analysis of AOA Localization and Optimal Heading Angles Generation Method for UAV Swarms |
| title_full_unstemmed | Optimal Configuration Analysis of AOA Localization and Optimal Heading Angles Generation Method for UAV Swarms |
| title_short | Optimal Configuration Analysis of AOA Localization and Optimal Heading Angles Generation Method for UAV Swarms |
| title_sort | optimal configuration analysis of aoa localization and optimal heading angles generation method for uav swarms |
| topic | AOA localization distributed collaborative autonomous generation (DCAG) Cramer-Rao low bound (CRLB) deep neural network (NN) |
| url | https://ieeexplore.ieee.org/document/8720270/ |
| work_keys_str_mv | AT weijiawang optimalconfigurationanalysisofaoalocalizationandoptimalheadinganglesgenerationmethodforuavswarms AT pengbai optimalconfigurationanalysisofaoalocalizationandoptimalheadinganglesgenerationmethodforuavswarms AT yuzhou optimalconfigurationanalysisofaoalocalizationandoptimalheadinganglesgenerationmethodforuavswarms AT xiaolongliang optimalconfigurationanalysisofaoalocalizationandoptimalheadinganglesgenerationmethodforuavswarms AT yubingwang optimalconfigurationanalysisofaoalocalizationandoptimalheadinganglesgenerationmethodforuavswarms |