A New Filling Algorithm of Missing Weather Radar Data

摘要：

To large missing data points in the weather radar data, this paper presented a missing data filling algorithm based on block and moving least squares surface fitting. First the information of missing points was achieved and missing points was initially interpolated according to the ordinary block-based least squares; then further adjusted every new value of the missing data by block-based and moving least squares surface fitting. Application examples prove that excellent filling value can be achieved by this algorithm. It well approximates the original data and smoothly transits to the neighbor points.

关键词： data filling least squares surface fitting

作者: Yunhong Pan Yun Zhang Ling Zhong Zhifang WU

作者单位: Faculty of Automation Guangdong University of Technology Guangzhou, Guangdong, China Guangzhou Central Observatory Guangdong Meteorological Bureau Guangzhou, Guangdong, China

会议类型: 国际会议

会议名称: 2010 Second Asia-Pacific Conference on Information Processing(2010年第二届亚太地区信息处理国际会议 APCIP 2010)

会议地点: 南昌

会议语种:英文

页码: 76-79

在线出版日期: 2010-09-17（万方平台首次上网日期，不代表论文的发表时间）