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粗差检测与抗差估计相结合的方法在动态相对定位中的应用 总被引:2,自引:0,他引:2
分析了粗差对GPS动态相对定位的影响,给出了相应的影响函数和抗差估计方法。建议采用粗差探测与抗差估计相结合的方法来处理GPS动态定位中的粗差问题。抗差估计中的等价权分别采用了IGG3方案和双因子等价权函数,对两种方案的效果进行比较和分析,并利用实测数据对所提方法的实际效果进行了检验。结果表明,基于粗差探测和抗差估计相结合的粗差处理方法可有效控制和抵御粗差的影响;分别采用IGG3方案和双因子等价权函数的定位结果差异较小。 相似文献
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抗差估计在粗差探测及平差计算中的应用 总被引:3,自引:0,他引:3
常规的粗差深测技术,不仅辅助计算工作量大,而且将粗差探测与平差计算分两步进行。本文根据抗差估计原理,通过对观测值附加粗差的办法,制订不同的方案,分别进行抗差估计和LS估计。 相似文献
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介绍了用差分算子和时间序列分析法建立数字化过程随机误差估计模型中的粗差探测方法和抗差估计方案。 相似文献
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Helmert方差分量估计的粗差检验与抗差解 总被引:10,自引:0,他引:10
当观测值中含有粗差时,检验表明Helmert方差分量估计结果同样含有粗差,且粗差还可能会发生转移,为有效地抵制粗差和随机模型差的互相影响,指出了发生这一转移的原因,介绍了基于双因子等价权的抗差估计,并针对相关Helmert方差分量估计抗差解求解过程中容易出现的法矩阵0值溢出问题,提出了改进方法。 相似文献
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粗差探测与定位的一种新方法 总被引:2,自引:0,他引:2
本文阐述了模型误差的可发现性与可区分性的重要性以及判别方法,提出一种利用观测值改正数向量综合分析的方法探测粗差。在模型误差可区分时可以对粗差定位并估计粗差值。同ω检验法比较,综合分析法发现粗差的能力更强,定位更准确。 相似文献
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Generalised measures of reliability for multiple outliers 总被引:2,自引:2,他引:0
The application of the theory of reliability has become a fundamental part of measurement analysis, whether in order to optimise
measurement systems so that they are resistant to the influence of outliers or in the post-analysis identification of outliers.
However, the current theory of reliability is based on the assumption of a single outlier—an assumption that may not necessarily
be the case. This paper extends reliability theory so that it can be applied to multiple outliers through the derivation of
appropriate measures of reliability for multiple outliers. The measures of reliability covered include minimal detectable
biases, reliability numbers, controllability, and external reliability. 相似文献
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Adaptively robust filtering for kinematic geodetic positioning 总被引:16,自引:0,他引:16
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强跟踪抗差自适应滤波算法及其在无人机导航定位中的应用 总被引:1,自引:0,他引:1
针对Sage-Husa自适应滤波算法在无人机导航定位应用中存在滤波发散和定位精度低的问题,本文提出一种强跟踪抗差自适应滤波算法.该算法在Sage-Husa自适应滤波算法基础上,引入强跟踪技术,通过自适应渐消因子降低历史数据对当前滤波的影响,从而抑制滤波发散,增强算法的稳健性;结合量测噪声和系统噪声进行实时估计,并且在估... 相似文献
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In integrated systems for accurate positioning, which consist of GNSS, INS, and other sensors, the GNSS positioning accuracy has a decisive influence on the performance of the entire system and thus is very important. However, GNSS usually exhibits poor positioning results in urban canyon environments due to pseudorange measurement errors caused by multipath creation, which leads to performance degradation of the entire positioning system. For this reason, in order to maintain the accuracy of an integrated positioning system, it is necessary to determine when the GNSS positioning is accurate and which satellites can have their pseudorange measured accurately without multipath errors. Thus, the objective of our work is to detect the multipath errors in the satellite signals and exclude these signals to improve the positioning accuracy of GNSS, especially in an urban canyon environment. One of the previous technologies for tackling this problem is RAIM, which checks the residual of the least square and identifies the suspicious satellites. However, it presumes a Gaussian measurement error that is more common in an open-sky environment than in the urban canyon environment. On the other hand, our proposed method can estimate the size of the pseudorange error directly from the information of altitude positioning error, which is available with an altitude map. This method can estimate even the size of non-Gaussian error due to multipath in the urban canyon environment. Then, the estimated pseudorange error is utilized to weight satellite signals and improve the positioning accuracy. The proposed method was tested with a low-cost GNSS receiver mounted on a test vehicle in a test drive in Nagoya, Japan, which is a typical urban canyon environment. The experimental result shows that the estimated pseudorange error is accurate enough to exclude erroneous satellites and improve the GNSS positioning accuracy. 相似文献
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针对传统多基线合成孔径雷达干涉相位估计方法存在稳健性不高、适应性不强的问题,该文提出一种稳健的多基线合成孔径雷达干涉相位估计方法。利用最大似然频率估计准则从最短基线干涉图中提取每一复像元随基线变化频率的粗略估计值,并把提取的粗略频率通过共轭复乘补偿给相应的抽样复干涉信号,来降低抽样复干涉信号频率,避免了干涉基线间隔过大导致的抽样复干涉信号频谱混叠现象,从而克服了干涉基线间隔对长基线干涉相位估计精度的限制。实验结果表明,该方法不受干涉基线间隔的限制,能较为精确地获得长基线干涉相位估计值,对多基线干涉合成孔径雷达技术应用拓展以及高精度地理信息系统构建等具有参考价值。 相似文献
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针对单目视觉/INS的组合定位算法中,单目视觉本身不具备尺度的问题以及在景深变化明显和光照不均匀的环境下会产生粗差的问题,提出了一种单目视觉/INS组合室内定位抗差方法。在尺度恢复方面,借助INS的位置增量信息,基于最小二乘法对单目视觉进行尺度恢复。在抗差方法方面,利用INS在短时间间隔内增量信息高精度的特性,对单目视觉在此时间间隔内的增量信息进行检测,判断是否产生粗差并进行粗差剔除,进而提高组合定位系统的定位精度。实验结果表明,所提算法可以有效的探测并剔除单目视觉/INS组合系统在恶劣环境下产生的粗差,提高组合定位系统的精度及鲁棒性。 相似文献