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朱建军, J. Zhu, , R. Santerre, X.-W. Chang
Journal of Geodesy (2005) 78: 528-534,-0001,():
-1年11月30日
One of the typical approaches to linear, inequality-constrained adjustment (LICA) is to solve a least-squares (LS) problem subject to the linear inequality constraints. The main disadvantage of this approach is that the statistical properties of the estimate are not easily determined and thus no general conclusions about the superiority of the estimate can be made. A new approach to solving the LICA problem is proposed. The linear inequality constraints are converted into priorinformation on the parameters with a uniform distribution, and consequently the LICA problem is reformulated into a Bayesian estimation problem. It is shown that the LS estimate of the LICA problem is identical to the Bayesian estimate based on the mode of the posterior distribution. Finally, the Bayesian method is applied to GPS positioning. Results for four field tests show that, when height information is used, the GPS phase ambiguity resolution can be improved significantly and the new approach is feasible.
Linearl inequality-constrained adjustment (, LICA), -Least-squares estimation-Bayesian estimation-Uniform prior distribution-GPS positioning
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朱建军, 丁晓利, 陈永奇
测绘学报,2003,8(3):261-266,-0001,():
-1年11月30日
首先假设边坡滑坡体为刚体,建立边坡滑坡的动态模型,由此建立卡尔曼滤波的系统方程。边坡的力学状态通过卡尔曼滤波与边坡变形观测的数据联系起来了。模型的不确定性(模型误差)是通过建立的虚拟观测方程来考虑的。与已有的方法不同的是,所建立的方法不仅利用包含在观测中的统计信息,而且能利用边坡滑坡的有关力学状态和地质条件所提供的信息。最后,以一实例论证方法的可行性。
动态滑坡监测模型, 卡尔曼滤波, 刚体假设, 滑坡监测
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朱建军, 郭光明, 符海华
矿冶工程,2002,3(1):1-3,-0001,():
-1年11月30日
研究了边坡滑移规律,指出滑移过程为缓慢蠕变→加速蠕变→缓慢蠕变→停止蠕变或缓慢蠕变→加速蠕变→突变→停止蠕变。然后选择了适合于变形分析的非线性回归模型,研究了非线性回归模型的计算方法。并辅以某边坡实测资料分析实例。
边坡监测, 蠕变, 非线性回归, 岭估计, Weibull模型
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【期刊论文】Dynamic model for landsliding monitoring under rigid body assumption①
朱建军, ZHU Jian jun, DING Xiao li, CHEN Yong qi
Trans. Nonferrous Met. Socd. China Apr. 2001 Vol.11 No.2,-0001,():
-1年11月30日
Based on the assumption that the slope bodies are rigid, the dynamic model of the landsiding (forward mod-el) was put forward. According to the dynamic model, the system equations of Kalman filter were constituted. The me-chanical status of a slope was hence combined with the monitoring data by Kalman filter. The model uncertainties or mod-el errors could also be considered through some fictitious observation equations. Different from existed methods, the pre-sented method can make use for not only the statistic information contained in the data but also the information provided by the mechanical and geological aspect of slopes. At last a numerical example was given out to show the feasibility of the method.
dynamic model, Kalman filter, rigid body, landslide monitoring
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