基于卡爾曼濾波的PS-InSAR地表形變預測方法
發(fā)布時間:2019-07-19 18:15
【摘要】:PS-In SAR是用于監(jiān)測大范圍地表形變的微波遙感技術,可提供精確地表形變信息,但該技術無法對形變趨勢進行預測,F(xiàn)有形變預測方法只能預測少數(shù)監(jiān)測點的形變,不適用于大面積預測。針對這些問題,提出一種基于卡爾曼濾波的PS-In SAR地表形變預測方法。結合PS-In SAR方法的技術流程,從理論上推導設計卡爾曼濾波器,通過真實的多時相SAR數(shù)據(jù)對該方法進行驗證。實驗結果表明,該算法可充分利用PS-In SAR形變監(jiān)測信息,有效預測大面積觀測區(qū)域的形變趨勢。
[Abstract]:PS-In SAR is a microwave remote sensing technology for monitoring large-scale surface deformation, which can provide accurate surface deformation information, but this technology can not predict the deformation trend. The existing deformation prediction methods can only predict the deformation of a few monitoring points, and are not suitable for large area prediction. In order to solve these problems, a PS-In SAR surface deformation prediction method based on Kalman filter is proposed. Combined with the technical flow of PS-In SAR method, the Kalman filter is deduced and designed theoretically, and the method is verified by real multi-temporal SAR data. The experimental results show that the algorithm can make full use of PS-In SAR deformation monitoring information to effectively predict the deformation trend of large area observation area.
【作者單位】: 中國科學院電子學研究所;中國科學院空間信息處理與應用系統(tǒng)技術重點實驗室;中國科學院大學;
【基金】:中國科學院“百人計劃”項目(Y53Z180390) 民政部國家減災中心項目(8435-01)資助
【分類號】:TP722.6
本文編號:2516420
[Abstract]:PS-In SAR is a microwave remote sensing technology for monitoring large-scale surface deformation, which can provide accurate surface deformation information, but this technology can not predict the deformation trend. The existing deformation prediction methods can only predict the deformation of a few monitoring points, and are not suitable for large area prediction. In order to solve these problems, a PS-In SAR surface deformation prediction method based on Kalman filter is proposed. Combined with the technical flow of PS-In SAR method, the Kalman filter is deduced and designed theoretically, and the method is verified by real multi-temporal SAR data. The experimental results show that the algorithm can make full use of PS-In SAR deformation monitoring information to effectively predict the deformation trend of large area observation area.
【作者單位】: 中國科學院電子學研究所;中國科學院空間信息處理與應用系統(tǒng)技術重點實驗室;中國科學院大學;
【基金】:中國科學院“百人計劃”項目(Y53Z180390) 民政部國家減災中心項目(8435-01)資助
【分類號】:TP722.6
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