A joint optimization algorithm for focused energy delivery in precision electronic warfare
Focused energy delivery (FED) is a technique that can precisely bring energy to the specific region, which arouses wide attention in precision electronic warfare (PREW). This paper first proposes a joint optimization model with respect to the locations of the array and the transmitted signals to imp...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co., Ltd.
2022-04-01
|
| Series: | Defence Technology |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214914721000271 |
| _version_ | 1811271749454528512 |
|---|---|
| author | Zhong-ping Yang Shu-ning Yang Qing-song Zhou Jian-yun Zhang Zhi-hui Li Zhong-rui Huang |
| author_facet | Zhong-ping Yang Shu-ning Yang Qing-song Zhou Jian-yun Zhang Zhi-hui Li Zhong-rui Huang |
| author_sort | Zhong-ping Yang |
| collection | DOAJ |
| description | Focused energy delivery (FED) is a technique that can precisely bring energy to the specific region, which arouses wide attention in precision electronic warfare (PREW). This paper first proposes a joint optimization model with respect to the locations of the array and the transmitted signals to improve the performance of FED. As the problem is nonconvex and NP-hard, particle swarm optimization (PSO) is adopted to solve the locations of the array, while designing the transmitted signals under a feasible array is considered as a unimodular quadratic program (UQP) subproblem to calculate the fitness criterion of PSO. In the PSO-UQP framework established, two methods are presented for the UQP subproblem, which are more efficient and more accurate respectively than previous works. Furthermore, a threshold value is set in the framework to determine which method to adopt to take full advantages of the methods above. Meanwhile, we obtain the maximum localization error that FED can tolerate, which is significant for implementing FED in practice. Simulation results are provided to demonstrate the effectiveness of the joint optimization algorithm, and the correctness of the maximum localization error derived. |
| first_indexed | 2024-04-12T22:26:40Z |
| format | Article |
| id | doaj.art-d6b49f3b076e44b2a7a584d707a1fe1d |
| institution | Directory Open Access Journal |
| issn | 2214-9147 |
| language | English |
| last_indexed | 2024-04-12T22:26:40Z |
| publishDate | 2022-04-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Defence Technology |
| spelling | doaj.art-d6b49f3b076e44b2a7a584d707a1fe1d2022-12-22T03:14:07ZengKeAi Communications Co., Ltd.Defence Technology2214-91472022-04-01184709721A joint optimization algorithm for focused energy delivery in precision electronic warfareZhong-ping Yang0Shu-ning Yang1Qing-song Zhou2Jian-yun Zhang3Zhi-hui Li4Zhong-rui Huang5Corresponding author.; College of Electronic Engineering, National University of Defense Technology, He Fei, ChinaCollege of Electronic Engineering, National University of Defense Technology, He Fei, ChinaCollege of Electronic Engineering, National University of Defense Technology, He Fei, ChinaCollege of Electronic Engineering, National University of Defense Technology, He Fei, ChinaCollege of Electronic Engineering, National University of Defense Technology, He Fei, ChinaCollege of Electronic Engineering, National University of Defense Technology, He Fei, ChinaFocused energy delivery (FED) is a technique that can precisely bring energy to the specific region, which arouses wide attention in precision electronic warfare (PREW). This paper first proposes a joint optimization model with respect to the locations of the array and the transmitted signals to improve the performance of FED. As the problem is nonconvex and NP-hard, particle swarm optimization (PSO) is adopted to solve the locations of the array, while designing the transmitted signals under a feasible array is considered as a unimodular quadratic program (UQP) subproblem to calculate the fitness criterion of PSO. In the PSO-UQP framework established, two methods are presented for the UQP subproblem, which are more efficient and more accurate respectively than previous works. Furthermore, a threshold value is set in the framework to determine which method to adopt to take full advantages of the methods above. Meanwhile, we obtain the maximum localization error that FED can tolerate, which is significant for implementing FED in practice. Simulation results are provided to demonstrate the effectiveness of the joint optimization algorithm, and the correctness of the maximum localization error derived.http://www.sciencedirect.com/science/article/pii/S2214914721000271Focused energy deliveryLocalization errorParticle swarm optimizationPrecision electronic warfareUnimodular quadratic program |
| spellingShingle | Zhong-ping Yang Shu-ning Yang Qing-song Zhou Jian-yun Zhang Zhi-hui Li Zhong-rui Huang A joint optimization algorithm for focused energy delivery in precision electronic warfare Defence Technology Focused energy delivery Localization error Particle swarm optimization Precision electronic warfare Unimodular quadratic program |
| title | A joint optimization algorithm for focused energy delivery in precision electronic warfare |
| title_full | A joint optimization algorithm for focused energy delivery in precision electronic warfare |
| title_fullStr | A joint optimization algorithm for focused energy delivery in precision electronic warfare |
| title_full_unstemmed | A joint optimization algorithm for focused energy delivery in precision electronic warfare |
| title_short | A joint optimization algorithm for focused energy delivery in precision electronic warfare |
| title_sort | joint optimization algorithm for focused energy delivery in precision electronic warfare |
| topic | Focused energy delivery Localization error Particle swarm optimization Precision electronic warfare Unimodular quadratic program |
| url | http://www.sciencedirect.com/science/article/pii/S2214914721000271 |
| work_keys_str_mv | AT zhongpingyang ajointoptimizationalgorithmforfocusedenergydeliveryinprecisionelectronicwarfare AT shuningyang ajointoptimizationalgorithmforfocusedenergydeliveryinprecisionelectronicwarfare AT qingsongzhou ajointoptimizationalgorithmforfocusedenergydeliveryinprecisionelectronicwarfare AT jianyunzhang ajointoptimizationalgorithmforfocusedenergydeliveryinprecisionelectronicwarfare AT zhihuili ajointoptimizationalgorithmforfocusedenergydeliveryinprecisionelectronicwarfare AT zhongruihuang ajointoptimizationalgorithmforfocusedenergydeliveryinprecisionelectronicwarfare AT zhongpingyang jointoptimizationalgorithmforfocusedenergydeliveryinprecisionelectronicwarfare AT shuningyang jointoptimizationalgorithmforfocusedenergydeliveryinprecisionelectronicwarfare AT qingsongzhou jointoptimizationalgorithmforfocusedenergydeliveryinprecisionelectronicwarfare AT jianyunzhang jointoptimizationalgorithmforfocusedenergydeliveryinprecisionelectronicwarfare AT zhihuili jointoptimizationalgorithmforfocusedenergydeliveryinprecisionelectronicwarfare AT zhongruihuang jointoptimizationalgorithmforfocusedenergydeliveryinprecisionelectronicwarfare |