CCD损伤状态的“猫眼”回波信息评估方法  

"Cat's eye"echo information assessment method of CCD damage status

作　　者：俞婷 牛春晖[1] 吕勇[1] Yu Ting;Niu Chunhui;Lv Yong(School of Instrument Science and Photoelectric Engineering,Beijing Information Science&Technology University,Beijing 100192,China)

机构地区：[1]北京信息科技大学仪器科学与光电工程学院,北京100192

出　　处：《红外与激光工程》2023年第5期406-414,共9页Infrared and Laser Engineering

摘　　要：CCD损伤状态与“猫眼”回波强度和偏振度为复杂非线性关系,无法单独根据强度或偏振度数值正确评估CCD损伤与否。结合多源信息融合技术与机器学习,利用适合非线性数据分类判别的KNN、K-SVM和PNN三种方法对CCD损伤状态评估方法进行研究。分别进行了近、远距离“猫眼”回波探测实验,以回波强度、偏振度信息和CCD实际损伤信息作为输入数据,分别对三种方法进行了训练,对比了训练的三种方法的评估测试结果,包括评估点的错误数量、错误率及评估时间,发现室外复杂环境时通过选择最优平滑因子σ的PNN方法错误率最低,在考虑实际评估允许时间范围内,PNN方法最适合用于基于“猫眼”回波信息的CCD损伤状态评估应用。Objective Charge Coupled Devices(CCD)is a common photoelectric sensor for acquiring image information in photoelectric warfare.In photoelectric warfare,active detection,optical performance analysis and damage status assessment of enemy CCD device are the prerequisites for effective implementation of photoelectric warfare.At present,there are few studies on CCD damage status and damage grade assessment based on the detection echo information,and the actual assessment is affected by the complex environment.The CCD damage status has a complex nonlinear relationship with the"cat's eye"echo intensity and polarization degree which can’t correctly judge whether the CCD is damaged or not based on the intensity and polarization value alone.Therefore,it is considered to use multi-source information fusion method to carry out research on CCD damage status assessment,that is,combining the characteristic information of multiple CCD to obtain the optimal estimation.Methods Combined with multi-source information fusion technology and machine learning,three models of KNN,K-SVM and PNN suitable for nonlinear data classification and discrimination are used to study the assessment method of CCD damage status.Among the three assessment methods,the KNN method uses the category of the proximity point to predict the category,the K-SVM method uses the hyperplane to predict the category and the PNN method uses a posterior probability density to predict categories.Results and Discussions The near-and long-distance"cat's eye"echo detection experiments were carried out respectively,and the echo intensity,polarization degree information and CCD actual damage information were used as input data to train the three models respectively(Tab.3),and the assessments of the three models were compared including the number of errors in the assessment points,the error rate and the assessment time(Fig.5-6),which show that the error rates of KNN and K-SVM fluctuate within 4%,and the error rate of PNN fluctuates within 2%during the five random test sets.

关 键 词：损伤评估 PNN CCD “猫眼”效应 偏振特性 

分 类 号：TN977[电子电信—信号与信息处理]