【摘要】：提出了一種基于貝葉斯模式識別的激光雷達(dá)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(xué)特征向量的選擇依據(jù)對灰霾粒子進(jìn)行識別分類。采用計(jì)算機(jī)仿真實(shí)現(xiàn)了該灰霾組分模式識別模型,并通過兩種自驗(yàn)證方法檢驗(yàn)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(dá)的適用性,凸顯了偏振高光譜分辨率激光雷達(dá)(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(xué)光電信息工程學(xué)系現(xiàn)代光學(xué)儀器國家重點(diǎn)實(shí)驗(yàn)室;
【基金】：國家自然科學(xué)基金(41305014) 教育部博士點(diǎn)基金(20130101120133) 浙江省教育廳科研項(xiàng)目(Y201329660) 浙江省“儀器科學(xué)與技術(shù)”重中之重學(xué)科開放基金(JL130113) 中央高�；究蒲袠I(yè)務(wù)費(fèi)專項(xiàng)資金(2013QNA5006) 現(xiàn)代光學(xué)儀器國家重點(diǎn)實(shí)驗(yàn)室創(chuàng)新基金(MOI201208)
【分類號】：TN958.98

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 陶宗明;劉東;鐘志慶;史博;聶森;麻曉敏;周軍;;Measurements of cirrus clouds with a three-wavelength lidar[J];Chinese Optics Letters;2012年05期

2 李學(xué)彬;徐青山;魏合理;胡歡陵;;氣溶膠消光系數(shù)與質(zhì)量濃度的相關(guān)性研究[J];光學(xué)學(xué)報(bào);2008年09期

3 宓云，

本文編號：2288090