{"title":"用于模拟多脉冲拉曼激光雷达水汽剖面分析的卡尔曼滤波","authors":"B.A. Kwaky","doi":"10.1109/SICE.1999.788589","DOIUrl":null,"url":null,"abstract":"Kalman filtering theory was used to analyse simulated and real water vapor profiles. The simulation of the Raman lidar water vapor profiles was based on the third harmonic of the Nd-YAG laser. The Kalman filter was applied to both single pulse and multipulse water vapor profiles corrupted by Gaussian white noise. The results obtained by the Kalman filter approach were later compared with conventional signal averaging techniques and the smoothing filter technique. In general, the Kalman filter out-performed the conventional filters in both its smoothing and predictive capabilities. The merits and demerits of the Kalman filter when applied for the analysis of atmospheric water vapor profiles are discussed.","PeriodicalId":103164,"journal":{"name":"SICE '99. Proceedings of the 38th SICE Annual Conference. International Session Papers (IEEE Cat. No.99TH8456)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Kalman filter for the analysis of simulated multipulse Raman lidar water vapor profiles\",\"authors\":\"B.A. Kwaky\",\"doi\":\"10.1109/SICE.1999.788589\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Kalman filtering theory was used to analyse simulated and real water vapor profiles. The simulation of the Raman lidar water vapor profiles was based on the third harmonic of the Nd-YAG laser. The Kalman filter was applied to both single pulse and multipulse water vapor profiles corrupted by Gaussian white noise. The results obtained by the Kalman filter approach were later compared with conventional signal averaging techniques and the smoothing filter technique. In general, the Kalman filter out-performed the conventional filters in both its smoothing and predictive capabilities. The merits and demerits of the Kalman filter when applied for the analysis of atmospheric water vapor profiles are discussed.\",\"PeriodicalId\":103164,\"journal\":{\"name\":\"SICE '99. Proceedings of the 38th SICE Annual Conference. International Session Papers (IEEE Cat. No.99TH8456)\",\"volume\":\"44 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1999-07-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SICE '99. Proceedings of the 38th SICE Annual Conference. International Session Papers (IEEE Cat. No.99TH8456)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SICE.1999.788589\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SICE '99. Proceedings of the 38th SICE Annual Conference. International Session Papers (IEEE Cat. No.99TH8456)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SICE.1999.788589","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Kalman filter for the analysis of simulated multipulse Raman lidar water vapor profiles
Kalman filtering theory was used to analyse simulated and real water vapor profiles. The simulation of the Raman lidar water vapor profiles was based on the third harmonic of the Nd-YAG laser. The Kalman filter was applied to both single pulse and multipulse water vapor profiles corrupted by Gaussian white noise. The results obtained by the Kalman filter approach were later compared with conventional signal averaging techniques and the smoothing filter technique. In general, the Kalman filter out-performed the conventional filters in both its smoothing and predictive capabilities. The merits and demerits of the Kalman filter when applied for the analysis of atmospheric water vapor profiles are discussed.