| 利用交互多模型的动态精密单点定位故障诊断算法 |
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| 引用本文： | 聂建亮,吴富梅,何正斌,张双成.利用交互多模型的动态精密单点定位故障诊断算法[J].武汉大学学报(信息科学版),2011(6). |
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| 作者姓名： | 聂建亮 吴富梅 何正斌 张双成 |
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| 作者单位： | 国家测绘局大地测量数据处理中心;长安大学地质工程与测绘学院;信息工程大学测绘学院;西安测绘研究所; |
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| 基金项目： | 国家自然科学基金资助项目(40774001,40841021); 国家863计划资助项目(2007AA12Z331) |
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| 摘 要： | 提出了一种基于相邻历元模型概率比的交互多模型方法,以提高故障诊断的效率,控制异常数据对定位结果的影响。首先,根据故障可能发生的情况建立交互多模型,以便对故障进行定位;然后,根据相邻历元的故障模型概率比对故障进行诊断,提高故障诊断的正确率;最后,根据抗差估计原理对故障进行处理,控制异常影响,提高动态精密单点定位的精度。以实测动态GPS数据为例,此模型可以提高故障诊断的正确率,控制异常影响,进而提高动态精密单点定位的精度。
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| 关 键 词： | 动态精密单点定位 交互多模型 模型概率 故障诊断 抗差估计 |
Detection and Diagnosis of Failures in Dynamic Precise Point Positioning Using Interacting Multiple Models |
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| NIE Jianliang, WU Fumei, HE Zhengbin ZHANG Shuangcheng.Detection and Diagnosis of Failures in Dynamic Precise Point Positioning Using Interacting Multiple Models[J].Geomatics and Information Science of Wuhan University,2011(6). |
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| Authors: | NIE Jianliang WU Fumei HE Zhengbin ZHANG Shuangcheng |
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| Institution: | NIE Jianliang1,2 WU Fumei3,4 HE Zhengbin2 ZHANG Shuangcheng2 (1 Geodetic Data Processing Center,State Bureau of Surveying and Mapping,334 East Youyi Road,Xi'an 710054,China)(2 School of Geological and Surveying Engineering,Chang'an University,126 Yanta Road,China)(3 Institute of Surveying and Mapping,Information Engineering University,66 Middle Longhai Road,Zhengzhou 450052,China)(4 Xi'an Research Institute of Surveying and Mapping,1 Middle Section,Yanta Road,China) |
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| Abstract: | Failures often exist in dynamic precise point positioning due to the effects of the environment or GPS receivers,so the precision will degrade quickly.Interacting multiple models(IMM) based on the ratio of the probability of failure models is introduced,in order to improve the efficiency of diagnosis,control the outlier's influences on the dynamic precise point positioning.In the new procedure,IMM including all failure models is used for correct detection and diagnosis of failures at first.Failures are dete... |
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| Keywords: | dynamic precise point positioning interacting multiple models(IMM) probability of model detection and diagnosis of failures robust estimation |
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