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| 序统计滤波估计检测海洋测深异常数据 | |
| 引用本文： | 李明叁,张杰,严怀志,刘雁春,吕志平,暴景阳.序统计滤波估计检测海洋测深异常数据[J].海洋测绘,2007,27(1):7-11. |
| 作者姓名： | 李明叁 张杰 严怀志 刘雁春 吕志平 暴景阳 |
| 作者单位： | 1. 海军大连舰艇学院,海测工程系,辽宁,大连,116018;辽宁工程技术大学,地理空间信息技术与应用实验室,辽宁,阜新,123000;解放军信息工程大学,测绘学院,河南,郑州,450052 2. 海军大连舰艇学院,海测工程系,辽宁,大连,116018;辽宁工程技术大学,地理空间信息技术与应用实验室,辽宁,阜新,123000 3. 上海海事局,海测大队,上海,200090 4. 解放军信息工程大学,测绘学院,河南,郑州,450052 |
| 基金项目： | 国家自然科学基金项目(40071070)和(40671161)，辽宁工程技术大学地理空间信息技术与应用实验室基金项目(2005002)，国家地球空间环境与大地测量教育部重点实验室基金项目(1469990324233-03-04) |
| 摘 要： | 根据海洋水深数据处理的要求，构建了海洋水深数据的序统计滤波模型，并根据水深异常数据的特点，提出了离差法判定水深异常数据，在遵循“舍深取浅”这一基本海洋数据处理原则基础上，设计了海洋水深异常数据检测的序统计滤波方案。实例分析表明，该滤波方案能够有效地检测并剔除零水深、负水深、孤立突跳水深，保留连续（个数多于（含）3个的）异常水深，在序统计滤波异常数据检测的基础上剔除粗差，能大幅提高粗差检测的效率。 |
| 关 键 词： | 序统计滤波 水深异常数据 “舍深取浅”原则 |
| 文章编号： | 1671-3044（2007）01-0007-05 |
| 修稿时间： | 2006-07-11 |
Order Statistics Filtering for Detecting Outliers in Depth Data Along a Sounding Line |
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| LI Ming-san,ZHANG Jie,YAN Huai-zhi,LIU Yan-chun,L Zhi-ping,BAO Jing-yang.Order Statistics Filtering for Detecting Outliers in Depth Data Along a Sounding Line[J].Hydrographic Surveying and Charting,2007,27(1):7-11. | |
| Authors: | LI Ming-san ZHANG Jie YAN Huai-zhi LIU Yan-chun L Zhi-ping BAO Jing-yang |
| Institution: | 1. Department of Hydrography and Cartography, Dalian Naval Academy, Dalian, Liaoning, 116018 ; 2. The Geomatics and Applications Laboratory, Liaoning Technical University, Fuxin, Liaoning, 123000 ; 3. Institute of Surveying and Mapping, Information Engineering University, Zhengzhou, Henan,450052 ; 4. Hydrographic Surveying Team, Shanghai Maritime Safety Administration, Shanghai,200090 |
| Abstract: | According to the special demands in processing depth data,the models based on order statistics filter were presented here to detect outliers in depths along a sounding line.However,there is a key problem of how to distinguish the outliers from good depths;it was solved by the size of the differences between a would-be-filtered point and its neighbor points.And then a complex method based on order statistics filter to detect outliers in depths was given out to meet the various needs in processing sounding data.At last,the method has been tested using observed data.The results show that the method could remove gross errors,zero and minus depths,and preserve consecutive(more than 3) false echoes.And it could help the surveyors find and remove outliers effectively. |
| Keywords: | order statistics filter sounding outliers the principle of preferring shallower to deeper |
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