Uniform and constant long-time wireless power transmission of multi-targets in local space based on time reversal

Zhang, Zhiyuan; Li, Bing; Liu, Shiqi; Zhang, Honglin; Hu, Bin‐Jie; Zhao, Deshuang; Wang, Chunan

doi:10.7498/aps.71.20211231

Cited by 5 publications

(3 citation statements)

References 28 publications

(21 reference statements)

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“…它的核心是将接收到的宽带信号做时间上的反转, 然后再发射. 由于时间反演电磁波在各类不同电磁环境下均具有时间-空间同步聚焦的电磁特性 [23] , 因此, 利用时间反演的时空同步聚焦特性, 时间反演近年来和能量传输 [24] 、目标追踪 [25] 、自适应波束聚焦阵列 [26] 以及智能表面和波束赋形等方向 [27] 相结合, 进行了一系列的研究. 电子科技大学的研究者在文献 [28]中利用平面电磁波照射偶极子阵列, 使用时间反演技术实现了偶极子阵列辐射方向图的自适应回溯.…”

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Time-inversion technique based correction of complex radome radiation beam distortion

An¹,

Ding²,

Wang³

2023

Acta Phys. Sin.

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The electromagnetic wave radiated by radome often occurs aiming angle deviation, beam distortion and other phenomena, due to the complex electromagnetic medium composition, special contour and complex working environment. For conventional optimization methods, harsh and complex situations increase its workload, especially the specific location parameter information is unknown. In this paper, a method with time-reversal technique for correcting the radiation beam distortion of the complex radome is proposed. With the time-reversal method, the concrete parameters of different positions for the radome and the surrounding environment information are not necessary to be determined in advance. The derivation shows that the environmental information is eliminated adaptively by the conjugate convolution operation, and it is proved by numerical operation that the signal of maximum radiation gain in target angle is time-reversal signal. Then based on the adaptive focusing properties of time-reversed electromagnetic waves, a top wedge radome and an icing working radome are studied as paradigms. The equal amplitude phase shifting method is set as the control group to highlight the advantages of time-reversal. In the end, the results show that the radiation beam aiming error can be reduced from ±10° to ±0.9° within ±45° scanning range for the top wedge radome in C-band. And the main beam annihilated has been converged again for the radome in the icing state. In addition, all the improvements are broadband, and the robustness of the entire radome system is enhanced by increased target angle energy caused by the directional of the array radiation being increased and the 3dB beamwidth being narrowed. This paper provides an effective method for the analysis of complex radomes and radio wave propagation in complex media.

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“…电子科技大学的研究者在文献 [28]中利用平面电磁波照射偶极子阵列, 使用时间反演技术实现了偶极子阵列辐射方向图的自适应回溯. 更深入研究发现, 丰富的多径信息可使上述聚焦效果更加明显 [23] , 且宽频带的时域信号通过时间反演会带来宽频带的聚焦效果 [29] .…”

Section: N P R E S Sunclassified

Time-inversion technique based correction of complex radome radiation beam distortion

An¹,

Ding²,

Wang³

2023

Acta Phys. Sin.

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“…As a result, the power lines will short-circuit after contact with trees, causing power outages and even fires in severe cases [2,3]. In order to avoid the adverse impacts of forest areas on the power corridor transmission system, efficiently obtaining tree species information in and around the transmission line corridor plays an important role in eliminating potential safety hazards [4,5]. The management of trees in power line corridors is a critical aspect in ensuring the uninterrupted flow of electricity and safeguarding communities from potential hazards.…”

Section: Introductionmentioning

confidence: 99%

Classification of Tree Species in Transmission Line Corridors Based on YOLO v7

Xu,

Wang,

Shi

et al. 2023

Forests

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The effective control of trees in transmission line corridors is crucial to mitigate the damage that they can cause to transmission lines. Investigating trees in these corridors presents a significant challenge, particularly in classifying individual tree species. Although the current deep learning model can segment single tree species, it exhibits low recognition accuracy in areas with dense forest canopies. The detection speed is also subject to limitations. To address these challenges, this study relies on aerial multispectral images obtained from drones as the primary data source. The process begins by extracting single tree crowns and establishing a sample dataset, divided in a 9:1 ratio into training and verification sets. Subsequently, the training set undergoes iterative parameter training using the YOLO v7 network. Once optimal parameters are obtained, the system outputs information on individual tree types. The verification sample set is then employed to assess the accuracy. Simultaneously, the YOLO v4 network model is applied to the same data, and the training results of the YOLO v7 network are compared and analyzed, revealing peak accuracy of 85.42% in recognizing single tree species. This approach provides an effective solution, offering reliable data for the in-depth investigation of trees in transmission line corridors and the accurate monitoring of concealed tree hazards.

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Comparison of Coprime Array and Uniform Array in Microwave Power Transfer Based on Time Reversal

Zhang

Liu

et al. 2022

2022 IEEE 5th International Conference on Electronics Technology (ICET)

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Uniform and constant long-time wireless power transmission of multi-targets in local space based on time reversal

Cited by 5 publications

References 28 publications

Time-inversion technique based correction of complex radome radiation beam distortion

Time-inversion technique based correction of complex radome radiation beam distortion

Classification of Tree Species in Transmission Line Corridors Based on YOLO v7

Comparison of Coprime Array and Uniform Array in Microwave Power Transfer Based on Time Reversal

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