张小红, 曾琪, 何俊, 康超. 构建阈值模型改善TurboEdit实时周跳探测[J]. 武汉大学学报 ( 信息科学版), 2017, 42(3): 285-292. DOI: 10.13203/j.whugis20150045
引用本文: 张小红, 曾琪, 何俊, 康超. 构建阈值模型改善TurboEdit实时周跳探测[J]. 武汉大学学报 ( 信息科学版), 2017, 42(3): 285-292. DOI: 10.13203/j.whugis20150045
ZHANG Xiaohong, ZENG Qi, HE Jun, KANG Chao. Improving TurboEdit Real-time Cycle Slip Detection by the Construction of Threshold Model[J]. Geomatics and Information Science of Wuhan University, 2017, 42(3): 285-292. DOI: 10.13203/j.whugis20150045
Citation: ZHANG Xiaohong, ZENG Qi, HE Jun, KANG Chao. Improving TurboEdit Real-time Cycle Slip Detection by the Construction of Threshold Model[J]. Geomatics and Information Science of Wuhan University, 2017, 42(3): 285-292. DOI: 10.13203/j.whugis20150045

构建阈值模型改善TurboEdit实时周跳探测

Improving TurboEdit Real-time Cycle Slip Detection by the Construction of Threshold Model

  • 摘要: 在比较现有各类TurboEdit改进算法的基础上,选取了一套适合实时周跳探测的组合方法,并针对其缺陷进行优化改进,加入阈值模型。在滑动平均滤波MW(Melborne-Wubbena)组合周跳探测方法中加入了自适应观测序列均方根变化的阈值模型,有效减少了周跳探测的误判和漏判;在相邻历元求差的GF(geometry-free)组合周跳探测中加入了随采样率及卫星高度角变化的加权阈值模型,显著提升了采样率较低时周跳探测的可靠性。大量数据测试检验表明,该组合方法有效可行,相比其他改进方法不仅在探测精度上有一定提高,在避免周跳误判、漏判上也有较大改善。

     

    Abstract: A combination method which is applicable to real-time cycle slip detection is selected based on the summary and comparison of various existing improved TurboEdit algorithms, and the method is optimized and improved by adding in the threshold models aiming at its defects. The specific optimizations are as follows: Adding the threshold model which is adaptive to the change of observation sequence RMS to the MW combination cycle slip detection based on the moving average filter, which reduces misjudgments and false negatives in the cycle slip detection effectively; Adding weighted threshold model which is changing with sampling rate and satellite elevation angle to the GF Combination cycle slip detection based on the GF difference between adjacent epochs, which improves the reliability of the cycle slip detection significantly when the sampling rate is low. A large amount of data are tested and the results show that, the combination method is effective and feasible. Compared with other improved methods, the method not only improves the detection precision to some extent, but also has great improvement in avoiding misjudgments and false negatives in cycle slip detection.

     

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