红外与毫米波学报, 2011, 30 (4): 350, 网络出版: 2011-08-18   

太赫兹宽频带准全向平板超材料吸波体的设计

Design of a wide-band and quasi-omnidirectional tabulate metamaterial absorber in the terahertz regime
作者单位
1 空军工程大学 理学院,陕西 西安710051
2 西安交通大学 电子陶瓷与器件教育部重点实验室,陕西 西安710049
3 空军工程大学 综合电子信息系统与电子对抗技术研究中心,陕西 西安710051
摘要
在太赫兹波段设计了一种宽频带准全向的平板超材料吸波体.仿真结果表明,该吸波体在4.36~4.91 THz之间具有极化不敏感和宽入射角的强吸收.提取的等效阻抗实部表明,可以通过调节超材料的电磁响应造成吸波体一侧与自由空间近似阻抗匹配、另一侧与自由空间阻抗不匹配,从而在吸收频带内同时实现反射率和传输率最小、吸收率最大.仿真的三种不同损耗情况下吸波体的吸收率表明,吸波体的强吸波特性主要源于金属损耗;金属无耗时,基板的介质损耗只能吸收部分能量.仿真的金属覆层在不同电导率和不同厚度情况下吸波体的吸收率表明,可以通过选用合适高电导率的金属以及适当减小金属覆层的厚度来加强金属损耗的强度.该吸波体可能在许多领域具有广泛的应用.
Abstract
We report the design of a wide-band and quasi-omnidirectional tabulate metamaterial absorber in the terahertz regime. Simulated results indicate that the absorber has a wide-band strong absorption between 4.36 and 4.91 THz, which is polarization insensitive and wide incident angle. Retrieved real parts of the impedance show that by adjusting the electromagnetic response of the metamaterial, the impedance of the absorber could be tuned to match approximatively the impedance of the free space on one side and do not match to the impedance of the free space on the other side, resulting in the minimal reflectance, the minimal transmission and the highest absorbance in the absorption band. Simulated absorbance values under three different loss conditions suggest that high absorbance is mainly due to metallic absorption and dielectric loss can be used to absorb partial energy if there is no metallic absorption. Simulated absorbance values under different electric conductivity values and copper thicknesses suggest that the intensity of metallic absorption can be boosted up by adopting metal of high conductivity or reducing the thickness of metal properly. This absorber may have broad applications in many scientific and technological fields.
参考文献

[1] HE You, WANG Guo-Hong, PENG Ying-Ning, et al. Multisensor Information Fusion with Application[M]. Beijing: Publication House of Electronics Industry(何友,王国宏,彭应宁,等.多传感器信息融合及应用.北京:电子工业出版社),2000.

[2] Maiter H, Bloch I. Image fusion[J]. Vistas in Astronomy,1997,41(3):329-335.

[3] Kumar P, Mittal A, Kumar P. Study of robust and intelligent surveillance in visible and multi-modal framework[J]. Informatica,2008,32:63-77.

[4] Dong J, Zhuang D F, Huang Y H, et al. Advances in multi-sensor data fusion: algorithm and applications[J]. Sensor,2009,9(10):7771-7784.

[5] Leykin A, Yang R, Hammoud R. Thermal-visible video fusion for moving target tracking and pedestrian classification[C]. In Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition -Workshops,2007:1-8.

[6] Lewis J J, Nikolov S G, Loza A, et al. The Eden Project multi-sensor data set[R]. University of Bristol, Waterfall Solutions Ltd, 2006.

[7] Cvejic N, Nikolov G S, Knowels D H, et al. The effect of pixel-level fusion on object tracking in multi-sensor surveillance video[C]. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition,2007:1-7.

[8] Davis J W, Sharma V. Background-subtraction using contour-based fusion of thermal and visible imagery[J]. Computer Vision and Image Understanding,2007,106(2-3):162-182.

[9] Sharma V, Davis J W. Feature-level fusion for object segmentation using mutual information[J]. Augmented Vision Perception in Infrared,2008,6:295-319.

[10] Ju H, Bhanu B. Fusion of color and infrared video for moving human detection[J]. Pattern Recognition,2007,40(6):1771-1784.

[11] Conaire C O, Cooke E, Connor O N, et al. Background modeling infrared and visible spectrum video for people tracking[C]. In Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition,2005:20.

[12] Torabi A, Mass e G, Bilodeau G A, Feedback scheme for thermal-visible video registration, sensor fusion, and people tracking[C]. In Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition -Workshops,2010:15-22.

[13] Conaire C O , Cooke E , Connor O N, et al. Fusion of infrared and visible spectrum for indoor surveillance[C]. In Proceedings of International Workshop on Image Analysis for Multimedia Interactive Service,2005:382.

[14] Leykin A, Hammoud R. Robust multi-pedestrian tracking in thermal-visible surveillance videos[C]. In Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition-Workshops, 2006:136.

[15] Bertozzi M, Broggi A, Felisa M, et al. Low-level pedestrian detection by means of visible and far infra-red tetra-vision[C]. In Proceedings of Intelligent Vehicles Symposium,2006:231-236.

[16] Shafer G. A mathematical theory of evidence[M]. Princeton: Princeton Univ. Press,1976.

[17] Smets Ph, Kennes R. The transferable belief model[J]. Artificial Intelligence,1994,66:191-243.

[18] Nadimi S, Bhanu B. Multistrategy fusion using mixture model for moving object detection[C]. In Proceedings of International Conference Multisensor Fusion and Integration for Intelligent Systems,2001:317-322.

[19] Kumar P, Mittal A, Kumar P. Addressing uncertainty in multi-modal fusion for improved object detection in dynamic environment[J]. Information Fusion,2010,11(4):311-324.

[20] Zhang Y N, Tong X M, Zhang X W, et al. Pedestrian detection based on multi-modal cooperation[C]. In Proceedings of International Workshop on Multimedia Signal Processing,2008:148-152.

[21] Denman S, Fookes C, Sridharan S, et al. Multi-modal object tracking using dynamic performance metrics[C].In 7th IEEE International Conference on Advanced Video and Signal-Based Surveillance,2010:286-293.

[22] Nadimi S, Bhanu B. Physics-based cooperative sensor fusion for moving object detection[C]. In Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition-Workshops, 2004,6:108.

[23] Jones D G, Allsop E R, Gilby H J. Bayesian analysis for fusion of data from disparate imaging systems for surveillance[J]. Image and Vision Computing,2003,21(10):843-849.

[24] Krotosky S J, Trivedi M M. Person surveillance using visual and infrared imagery[J]. IEEE Transaction on Circuits and Systems for Video Technology,2008,18(8):1096-1105.

[25] Krotosky S J, Trivedi M M. On color-, infrared-, and multimodal-stereo approaches to pedestrian detection[J]. IEEE Transaction on Intelligent Transportation System,2007,8(4):619-629.

[26] Rogova G, Nimier V. Reliability in information fusion: literature survey[C]. In Proceedings of International Conference on Information Fusion,2004:1158-1165.

[27] Rand B P, Peumans P, Forrest S R. Long-range absorption enhancement in organic tandem thin-film solar cells containing silver nanoclusters[J]. J. Appl. Phys.,2004,96(12):7519-7526.

[28] Pillai S, Catchpole K R, Trupke T, et al. Surface plasmon enhanced silicon solar cells[J]. J. Appl. Phys.,2007,101(9):3105-3112.

[29] Zhou J F, Zhang L, Tuttle G, et al. Negative index materials using simple short wire pairs[J]. phys. Rev. B.,2006,73(4):1101-1104.

[30] Chen X, Grzegorczyk T M, Wu B, et al. Robust method to retrieve the constitutive effective parameters of metamaterials[J]. Phys. Rev. E,2004,70(1):6608-6614.

顾超, 屈绍波, 裴志斌, 徐卓, 柏鹏, 彭卫东, 林宝勤, 周航. 太赫兹宽频带准全向平板超材料吸波体的设计[J]. 红外与毫米波学报, 2011, 30(4): 350. GU Chao, QU Shao-Bo, PEI Zhi-Bin, XU Zhuo, BAI Peng, PENG Wei-Dong, LIN Bao-Qin, ZHOU Hang. Design of a wide-band and quasi-omnidirectional tabulate metamaterial absorber in the terahertz regime[J]. Journal of Infrared and Millimeter Waves, 2011, 30(4): 350.

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