【摘要】：提出了一種基于貝葉斯模式識別的激光雷達大氣遙感灰霾組分識別的方法。介紹了灰霾組分模式識別模型的建立過程,并利用具體的貝葉斯判別函數(shù)作為灰霾粒子光學特征向量的選擇依據(jù)對灰霾粒子進行識別分類。采用計算機仿真實現(xiàn)了該灰霾組分模式識別模型,并通過兩種自驗證方法檢驗了模型的正確性和穩(wěn)定性。討論了該模型對現(xiàn)有大氣遙感激光雷達的適用性,凸顯了偏振高光譜分辨率激光雷達(HSRL)的優(yōu)勢。
[Abstract]:A method based on Bayesian pattern recognition (Bayesian pattern recognition) for atmospheric remote sensing of haze components in lidar is proposed. This paper introduces the establishment of haze component pattern recognition model and classifies haze particles according to the selection of optical eigenvector of haze particles by using specific Bayesian discriminant function (Bayesian discriminant function). The model of haze component pattern recognition is realized by computer simulation, and the correctness and stability of the model are verified by two self-verification methods. The applicability of the model to the existing atmospheric remote sensing lidar is discussed, which highlights the advantages of polarization hyperspectral resolution lidar (HSRL).
【作者單位】： 浙江大學光電信息工程學系現(xiàn)代光學儀器國家重點實驗室;
【基金】：國家自然科學基金(41305014) 教育部博士點基金(20130101120133) 浙江省教育廳科研項目(Y201329660) 浙江省“儀器科學與技術”重中之重學科開放基金(JL130113) 中央高�；究蒲袠I(yè)務費專項資金(2013QNA5006) 現(xiàn)代光學儀器國家重點實驗室創(chuàng)新基金(MOI201208)
【分類號】：TN958.98

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