公开(公告)号：US10439594B2

公开(公告)日：2019-10-08

申请号：US15519823

申请日：2014-12-01

申请人： Yuxin Zhao ,  HARBIN ENGINEERING UNIVERSITY

发明人： Yuxin Zhao ,  Chang Liu ,  Xuefeng Zhang ,  Liqiang Liu ,  Gang Li ,  Feng Gao ,  Ning Li ,  Zhifeng Shen ,  Zhenxing Zhang ,  Zhao Qi

IPC分类号： G06F17/50 ,  H03H17/02

摘要： The present invention provides an actually-measured marine environment data assimilation method based on sequence recursive filtering three-dimensional variation. The method includes: preprocessing actually-measured marine environment data; calculating a target function value; calculating a gradient value of a target function; calculating a minimum value of the target function; extracting space multi-scale information from the actually-measured data; and updating background field data to form a final data assimilation analysis field. The present invention improves the traditional recursive filtering three-dimensional variation method, and sequentially assimilates information with different scales, thereby effectively overcoming the problem that multi-scale information cannot be effectively extracted by a traditional three-dimensional variation method. A high-order recursive Gaussian filter is used, and a cascaded form of the high-order recursive filter is converted into a parallel structure, so that the recursive filtering process of the recursive Gaussian filter can be executed in parallel, and many problems caused by a cascaded filter are overcome.

公开(公告)号：US20170338802A1

公开(公告)日：2017-11-23

申请号：US15519823

申请日：2014-12-01

申请人： HARBIN ENGINEERING UNIVERSITY

发明人： Yuxin Zhao ,  Chang Liu ,  Harbin, Heilongjiang Zhang ,  Liqiang Liu ,  Gang Li ,  Feng Gao ,  Ning Li ,  Zhifeng Shen ,  Zhenxing Zhang ,  Zhao Qi

IPC分类号： H03H17/02

CPC分类号： H03H17/0282 ,  G06F17/50 ,  H03H17/0202 ,  H03H2017/021

摘要： The present invention provides an actually-measured marine environment data assimilation method based on sequence recursive filtering three-dimensional variation. The method includes: preprocessing actually-measured marine environment data; calculating a target function value; calculating a gradient value of a target function; calculating a minimum value of the target function; extracting space multi-scale information from the actually-measured data; and updating background field data to form a final data assimilation analysis field. The present invention improves the traditional recursive filtering three-dimensional variation method, and sequentially assimilates information with different scales, thereby effectively overcoming the problem that multi-scale information cannot be effectively extracted by a traditional three-dimensional variation method. A high-order recursive Gaussian filter is used, and a cascaded form of the high-order recursive filter is converted into a parallel structure, so that the recursive filtering process of the recursive Gaussian filter can be executed in parallel, and many problems caused by a cascaded filter are overcome.