基于红外光谱的点目标特征提取与识别  

Feature Acquisition and Recognition of Point Target Based on Infrared Spectrum

作　　者：李素钧 廖胜[1] 任栖锋[1] 李强[1] 

机构地区：[1]中国科学院光电技术研究所,成都610209 [2]中国科学院大学,北京100049

出　　处：《光电工程》2016年第5期15-19,共5页Opto-Electronic Engineering

基　　金：国防预研项目

摘　　要：针对观测远距离目标时,难以有效提取目标温度、面积、表面材料等特征信息的问题,本文从代表物体固有属性的光谱发射率出发,综合考虑目标的材料特征、结构特性、红外辐射特性等因素,建立了目标的双波段红外光谱复合模型,提出了基于材料光谱发射率的目标特征提取的方法。针对特定类型目标查找其表面主要构成材料,测量材料的光谱发射率,建立相应的数据库。在此基础上,利用鸡群算法对模型进行求解,反演得到目标的表面构成材料,辐射温度以及有效辐射面积,取得了良好的效果。In detection of distant target, it is difficult to extract target information effectively, which are the temperature, area, surface material type and other characteristics. According to the spectral emissivity, which is the inherent nature of an object, target material characteristics, structural characteristics and the infrared radiation characteristics, an IR composite model is established based on two wavebands. Based on the model and material spectral emissivity, a method of feature extraction of target is proposed. In terms of the special target, the main categories of constituent materials used in constructing them are found. Meantime, the spectral emissivity of materials is measured. The correspondent database is established, which describes the relationship between the categories of constituent materials and spectral emissivity of materials. Based on the model and database, surface material type, radiant temperature and effective radiation area of target are obtained by using chicken swarm algorithm. The method has a good result

关 键 词：红外光谱 光谱发射率 红外辐射 鸡群算法 反演 

分 类 号：TN247[电子电信—物理电子学]