罗志才, 周波阳, 钟波, 吴怿昊. 卫星重力梯度测量数据的粗差探测[J]. 武汉大学学报 ( 信息科学版), 2012, 37(12): 1392-1396.
引用本文: 罗志才, 周波阳, 钟波, 吴怿昊. 卫星重力梯度测量数据的粗差探测[J]. 武汉大学学报 ( 信息科学版), 2012, 37(12): 1392-1396.
LUO Zhicai, ZHOU Boyang, ZHONG Bo, WU Yihao. Outlier Detection of Satellite Gravity Gradiometry Data[J]. Geomatics and Information Science of Wuhan University, 2012, 37(12): 1392-1396.
Citation: LUO Zhicai, ZHOU Boyang, ZHONG Bo, WU Yihao. Outlier Detection of Satellite Gravity Gradiometry Data[J]. Geomatics and Information Science of Wuhan University, 2012, 37(12): 1392-1396.

卫星重力梯度测量数据的粗差探测

Outlier Detection of Satellite Gravity Gradiometry Data

  • 摘要: 分别讨论了阈值法、Dixon检验法和小波算法应用于卫星重力梯度数据粗差探测的效果。为了克服这3种单一粗差探测方法的不足,提出了卫星重力梯度数据的粗差探测组合方案,即联合Dixon检验和小波算法,以及联合Dixon检验、阈值法和小波算法的组合方案。模拟结果表明,两种组合方案均能有效改善粗差探测的效果。

     

    Abstract: Outlier detection is one of the key processes to data preprocessing of satellite gravity gradiometry(SGG),and its objective is to obtain high quality SGG data.The performance of thresholding,Dixon test and wavelet algorithm was discussed in the outlier detection of SGG data.And two combined schemes were presented to overcome some deficiencies of these three methods,namely the combination of Dixon test and wavelet algorithm,and that of Dixon test,thresholding and wavelet algorithm.The simulation results show that both the two combined schemes can improve the quality of outlier detection effectively.

     

/

返回文章
返回