Abstract：Imaging spectrum technology can obtain the image and spectral characteristics of the target at the same time, and it is easy to identify the traditional camouflage materials whose spectrum are different from the background spectrum. In recent years, imaging spectrum has been developed rapidly, which has experienced the leap from multispectral technology to hyperspectral technology. Owing to the application of ISR UAV technology in various countries, hyperspectral sensors are expanded from spaceborne to airborne, which can identify military camouflage targets in a closer range, and pose a huge challenge to the survival ability of military targets with important value. At present, the main design idea of hyperspectral camouflage materials is to composite materials with similar color and spectral reflection characteristics (within the detection range of sensors), so as to achieve “the same color and spectrum” with the environmental background to avoid the high spectrum reconnaissance. Green vegetation is the most common camouflage background, and it is also the spectral simulation object of most researches in this field. Its spectral reflection curve has four main characteristics in the visible near-infrared range: “green peak”, “red edge”, “near-infrared plateau” and “water absorption band”, assign to leaf tissue structure, chlorophyll and water. The photothermal stability of chlorophyll in vitro is poor, which cannot be directly used as camouflage material, so it is one of the current researches focuses on finding and synthesizing molecules with good stability, chlorophyll-like structure and spectrum. In addition, chrome green and cobalt green are commonly used camouflage pigments, which have spectral reflection characteristics similar to green vegetation, like “green peak”, “red edge” and “near-infrared plateau”. Researchers composited them with superabsorbent fillers to introduce “water absorption peak”, roughly simulating the reflection spectrum of green vegetation, but there are still some problems to be solved in order to achieve accurate simulation. Based on the Vis-NIR reflection spectra of green vegetation, this paper elucidated the material selection, which simulating spectrum properties of green vegetation in the visible and near-infrared region respectively, introduced the problems existing in the accurate simulation of the vegetation spectra, and the research work of improving the spectral similarity and weather ability through modification and composition. The prospects for the future developments are also discussed.
[1] ZHANG Chao-yang, CHENG Hai-feng, CHEN Zhao-hui, et al(张朝阳, 程海峰, 陈朝辉, 等). Electro-Optic Technology Application(光电技术应用), 2008，(1): 10.
[2] CHENG Hai-feng(程海峰). Performance Test and Evaluation of Camouflage Materials(伪装装饰材料性能检测与评价). Changsha：National University of Defense Technology Press(长沙：国防科技大学出版社), 2012.
[3] TONG Qing-xi, ZHANG Bing, ZHANG Li-fu(童庆禧, 张 兵, 张立福). Jounal of Remote Sensing(遥感学报), 2016, 20(5): 689.
[4] LI Hao, XUE Jun-jie, WANG Han-zhong(李 浩, 薛俊杰, 王晗中). Areodynamic Missile Journal(飞航导弹), 2020, (1): 76.
[5] CHEN Xu-guang, JIA Jun-jun, LI Chang-xi, et al(陈旭光, 贾军军, 李昌玺, 等). Areodynamic Missile Journal(飞航导弹), 2020, DOI: 10.16338/j.issn.1009-1319.20190290.
[6] LIU Zhi-ming, HU Bi-ru, WU Wen-jian, et al(刘志明, 胡碧茹, 吴文健, 等). Acta Photonica Sinica(光子学报), 2009, 38(4): 885.
[7] MA Li-fang, SHI Jia-ming, CHEN Zong-sheng(马丽芳, 时家明, 陈宗胜). Infrared Technology(红外技术), 2010, 32(5): 268.
[8] Jacquemoud S, Ustin S L, Verdebout J, et al. Remote Sensing of Environment, 1996, 56(3): 194.
[9] WANG Ji-hua, ZHAO Chun-jiang, HUANG Wen-jiang, et al(王纪华，赵春江，黄文江, 等). Basis and Application of Agricultural Quantitative Remote Sensing(农业定量遥感基础与应用). Beijing：Science Press(北京：科学出版社), 2008.
[10] Knipling E B. Remote Sensing of Environment, 1970, 1(3): 155.
[11] GUO Li, XU Guo-yue, LI Cheng, et al(郭 利, 徐国跃, 李 澄, 等). Infrared Technology(红外技术), 2012, 34(10): 588.
[12] LI Min, LI Cheng, ZHENG Shun-li, et al(李 敏, 李 澄, 郑顺丽, 等). Infrared Technology(红外技术), 2015, 37(9): 788.
[13] GUO Hai-rong, WANG Xiao-fei, LI Yuan-yuan(郭海蓉, 王晓飞, 李媛媛). Hubei Agricultural Sciences(湖北农业科学), 2011, 50(16): 3381.
[14] LIU Zu-wu, LUO Xuan, TIE Shao-long(刘祖武, 罗 璇, 铁绍龙). Natural Science Journal of Xiangtan University(湘潭大学自然科学学报), 1992，(1): 90.
[15] XU Hao, LIU Hang(许 浩, 刘 珩). Chinese Optics(中国光学), 2018, 11(5): 765.
[16] YANG Ling, LI Cheng, ZHANG Man-xin, et al(杨 玲, 李 澄, 张曼昕, 等). Infrared Technology(红外技术), 2018, 40(9): 915.
[17] Liu Z M, Wu W J, Hu B R. Science China: Technological Sciences, 2008, 51(11): 1902.
[18] Ardit M, Dondi M, Cruciani G, et al. Materials Research Bulletin, 2009, 44(3): 666.
[19] Eliziário S A, de Andrade J M, Lima J G, et al. Materials Chemistry and Physics, 2011, 129(1): 619.
[20] Li Y Q, Mei S G, Byon Y J, et al. ACS Sustainable Chemistry & Engineering, 2014, 2(2): 318.
[21] Tena M A, Meseguer S, Gargori C, et al. Journal of the European Ceramic Society, 2007, 27(1): 215.
[22] Zhou Y X, Weng X L, Yuan L, et al. Journal of the Ceramic Society of Japan, 2014, 122(1425): 311.
[23] Chen L, Weng X L, Deng L J. Preparation and Characterization of Cr<sub>2</sub>O<sub>3</sub>—TiO<sub>2</sub>—Co<sub>2</sub>O<sub>3</sub>—ZnO Green Pigment. Energy Science and Applied Technology-Fang (ed.). 2016 Taylor & Francis Group, London, ISBN 978-1-138-02833-3.
[24] Qin R, Xu G Y, Guo L, et al. Materials Chemistry and Physics, 2012, 136(2): 737.
[25] LIU Zhi-ming, WU Wen-jian, ZHANG Yong(刘志明，吴文建，张 勇). Journal of Functional Materials(功能材料)，2007，38：198.
[26] Yang Y J, Liu Z M, Hu B R, et al. Journal of Bionic Engineering, 2010, 7: S43.
[27] JIANG Xiao-jun, WANG Hua-lin, LING Jun, et al(蒋晓军, 王华林, 凌 军, 等). Acta Armamentarii(兵工学报), 2017, 38(2): 345.
[28] Gao Y, Ye H. International Journal of Heat and Mass Transfer, 2017, 114: 115.
