As artificial intelligence algorithm was introduced into target detection, the detection of spatial infrared dim targets could be classified as the binary problem of fuzzy detection. According to the detection model of infrared dim target in the air, a signal voltage ratio spectrum model was established. The simulation analysis showed that the variation trend of voltage ratio was related to the speed, attitude of the target and the two-machine posture, which could be used to detect the target. The dynamic characteristics building theory was adopted to build the bicolor ratio feature space of infrared dim target. Based on this feature space, the least squares classification algorithm was optimized to identify the objects from the spectral signal hierarchy. This method not only reduces the amount of the sample data, but also prevents the phenomenon of over-fitting caused by the parameter selection of Gaussian kernel function. It ensures the classification accuracy and improves the classification efficiency nearly doubled. Reference basis is provided for infrared dim target detection by artificial intelligence algorithm.
Key words
multispectral detection /
least squares classification algorithm /
bicolor ratio feature space /
dim target identification
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References
汪朝群. 雷达/红外成像双模导引头的联合探测概率研究[J]. 红外与激光工程,2003,32(3):221-225.
祁蒙. 红外搜索跟踪系统的探测概率研究[J]. 激光与红外,2004,34(4):269-271.
王芳, 寇添, 寇人可, 等. 变阈噪比优化机载IRST系统探测概率包线[J]. 光学学报,2019,39(3):0304002.
张翔, 张建奇, 秦翰林, 等. 采用多分辨率分解的高光谱图像异常检测[J]. 红外与激光工程,2011,40(3):570-575.
王海晏. 红外辐射及应用[M]. 西安: 西安电子科技大学出版社, 2014: 40-51.
吴晗平. 红外搜索系统[M]. 北京: 国防工业出版社, 2013: 217-239.
张建奇. 红外物理[M]. 西安: 西安电子科技大学出版社, 2013: 50-57.
寇人可, 王海晏, 吴学铭. 机载红外搜索跟踪系统的最佳阈噪比研究[J]. 光学学报,2017,37(3):0304001.
许永伟. 图解机器学习[M]. 北京: 人民邮电出版社, 2014: 98-105.
杉山将. 图解机器学习[M]. 许永伟, 译. 北京
KOU T, ZHOU Z L, LIU H Q, et al. Multispectral radiation envelope characteristics of aerial infrared point targets[J]. Optics and Laser Technology,2018(103):251-259.
WANG Chaoqun. Study on joint probability of detection for radar/IR integrated dual-model seeker[J]. Infrared and Laser Engineering,2003,32(3):221-225.
QI Meng. Detection probability of IR search and track system[J]. Laser & Infrared,2004,34(4):269-271.
WANG Fang, KOU Tian, KOU Renke, et al. Detection probability envelope of airborne irst system after variable threshold noise ratio optimization[J]. Acta Optica Sinica,2019,39(3):0304002.
REED I S, YU X. Adaptive multiple-band CFAR detection of an optical pattern with unknown spectral distribution[J]. IEEE Transactions on Acoustics, Speech, and Signal Processing,1990,38(10):1760-1770.
ZHANG Xiang, ZHANG Jianqi, QIN Hanlin, et al. Anomaly detection for hyperspectral image based on multiresolution decomposition[J]. Infrared and Laser Engineering,2011,40(3):570-575.
LI W, DU
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