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1.
An algorithm for considering time-correlated errors in a Kalman filter is presented. The algorithm differs from previous implementations
in that it does not suffer from numerical problems; does not contain inherent time latency or require reinterpretation of
Kalman filter parameters, and gives full consideration to additive white noise that is often still present but ignored in
previous implementations. Simulation results indicate that the application of the new algorithm yields more realistic and
therefore useful state and covariance information than the standard implementation. Results from a field test of the algorithm
applied to the problem of kinematic differential GPS demonstrate that the algorithm provides slightly pessimistic covariance
estimates whereas the standard Kalman filter provides optimistic covariance estimates. 相似文献
2.
提出了Winkler地基参数的Kalman滤波识别方法。引入Mindlin理论后,推导了Winkler地基上板的控制微分方程。利用Fourier变换,推求了Winkler地基上简支板的Fourier闭式解。推导了Winkler地基参数的Kalman滤波方程,研究了Winkler地基参数的Kalman滤波识别的具体计算步骤。研究表明,运用Kalman滤波理论进行Winkler地基参数的识别,能有效地估计Winkler地基参数;Winkler地基参数的滤波收敛速度和精度受地基参数初始值选取和位移实测资料的影响,且Kalman滤波理论也可用于其他地基模型地基参数的识别。 相似文献
3.
4.
Parameter sensitivity of three Kalman filter schemes for assimilation of water levels in shelf sea models 总被引:2,自引:0,他引:2
In applications of data assimilation algorithms, a number of poorly known assimilation parameters usually need to be specified. Hence, the documented success of data assimilation methodologies must rely on a moderate sensitivity to these parameters. This contribution presents a parameter sensitivity study of three well known Kalman filter approaches for the assimilation of water levels in a three dimensional hydrodynamic modelling system. The filters considered are the ensemble Kalman filter (EnKF), the reduced rank square root Kalman filter (RRSQRT) and the steady Kalman filter. A sensitivity analysis of key parameters in the schemes is undertaken for a setup in an idealised bay. The sensitivity of the resulting root mean square error (RMSE) is shown to be low to moderate. Hence the schemes are robust within an acceptable range and their application even with misspecified parameters is to be encouraged in this perspective. However, the predicted uncertainty of the assimilation results are sensitive to the parameters and hence must be applied with care. The sensitivity study further demonstrates the effectiveness of the steady Kalman filter in the given system as well as the great impact of assimilating even very few measurements. 相似文献
5.
6.
V. Carmillet J. -M. Brankart P. Brasseur H. Drange G. Evensen J. Verron 《Ocean Modelling》2001,3(3-4)
Within the European DIADEM project, a data assimilation system for coupled ocean circulation and marine ecosystem models has been implemented for the North Atlantic and the Nordic Seas. One objective of this project is to demonstrate the relevance of sophisticated methods to assimilate satellite data such as altimetry, surface temperature and ocean color, into realistic ocean models. In this paper, the singular evolutive extended Kalman (SEEK) filter, which is an advanced assimilation scheme where three-dimensional, multivariate error statistics are taken into account, is used to assimilate ocean color data into the biological component of the coupled system. The marine ecosystem model, derived from the FDM model [J. Mar. Res. 48 (1990) 591], includes 11 nitrogen and carbon compartments and describes the synthesis of organic matter in the euphotic zone, its consumption by animals of upper trophic levels, and the recycling of detritic material in the deep ocean. The circulation model coupled to the ecosystem is the Miami isopycnic coordinate ocean model (MICOM), which covers the Atlantic and the Arctic Oceans with an enhanced resolution in the North Atlantic basin. The model is forced with realistic ECMWF ocean/atmosphere fluxes, which permits to resolve the seasonal variability of the circulation and mixed layer properties. In the twin assimimation experiments reported here, the predictions of the coupled model are corrected every 10 days using pseudo-measurements of surface phytoplankton as a substitute to chlorophyll concentrations measured from space. The diagnostics of these experiments indicate that the assimilation is feasible with a reduced-order Kalman filter of small rank (of order 10) as long as a sufficiently good identification of the error structure is available. In addition, the control of non-observed quantities such as zooplankton and nitrate concentrations is made possible, owing to the multivariate nature of the analysis scheme. However, a too severe truncation of the error sub-space downgrades the propagation of surface information below the mixed layer. The reduction of the actual state vector to the surface layers is therefore investigated to improve the estimation process in the perspective of sea-viewing wide field-of-view sensor (SeaWiFS) data assimilation experiments. 相似文献
7.
A primitive equation model and a statistical predictor are coupled by data assimilation in order to combine the strength of both approaches. In this work, the system of two-way nested models centred in the Ligurian Sea and the satellite-based ocean forecasting (SOFT) system predicting the sea surface temperature (SST) are used. The data assimilation scheme is a simplified reduced order Kalman filter based on a constant error space. The assimilation of predicted SST improves the forecast of the hydrodynamic model compared to the forecast obtained by assimilating past SST observations used by the statistical predictor. This study shows that the SST of the SOFT predictor can be used to correct atmospheric heat fluxes. Traditionally this is done by relaxing the model SST towards the climatological SST. Therefore, the assimilation of SOFT SST and climatological SST are also compared. 相似文献
8.
9.
Engineering projects that require deformation monitoring frequently utilize geodetic sensors to measure displacements of target
points located in the deformation zone. In situations where control stations and targets are separated by a kilometer or more,
GPS can offer higher precision position updates at more frequent intervals than can normally be achieved using total station
technology. For large-scale deformation projects requiring the highest precision, it is therefore advisable to use a combination
of the two sensors. In response to the need for high precision, continuous GPS position updates in harsh deformation monitoring
environments, a software has been developed that employs triple-differenced carrier-phase measurements in a delayed-state
Kalman filter. Two data sets were analyzed to test the capabilities of the software. In the first test, a GPS antenna was
displaced using a translation stage to mimic slow deformation. In the second test, data collected at a large open pit mine
were processed. It was shown that the delayed-state Kalman filter developed could detect millimeter-level displacements of
a GPS antenna. The actual precision attained depends upon the amount of process noise infused at each epoch to accommodate
the antenna displacements. Higher process noise values result in quicker detection times, but at the same time increase the
noise in the solutions. A slow, 25 mm displacement was detected within 30 min of the full displacement with sigma values in
E, N and U of ±10 mm or better. The same displacement could also be detected in less than 5 h with sigma values in E, N and U of ±5 mm or better. The software works best for detecting long period deformations (e.g., 20 mm per day or less) for which
sigma values of 1–2 mm are attained in all three solution components. It was also shown that the triple-differenced carrier-phase
observation can be used to significantly reduce the effects of residual tropospheric delay that would normally plague double-differenced
observations in harsh GPS environments.
相似文献
Don KimEmail: |
10.
Ben K. H. Soon Steve Scheding Hyung-Kuen Lee Hung-Kyu Lee Hugh Durrant-Whyte 《GPS Solutions》2008,12(4):261-271
This paper presents a simple and effective approach that incorporates single-frequency, L1 time-differenced GPS carrier phase
(TDCP) measurements without the need of ambiguity resolution techniques and the complexity to accommodate the delayed-state
terms. Static trial results are included to illustrate the stochastic characteristics and effectiveness of the TDCP measurements
in controlling position error growth. The formulation of the TDCP observation model is also described in a 17-state tightly-coupled
GPS/INS iterative, extended Kalman filter (IEKF) approach. Preliminary land vehicle trial results are also presented to illustrate
the effectiveness of the TDCP which provides sub-meter positional accuracies when operating for more than 10 min. 相似文献