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191.
K. S. Rao Y. S. Rao H. K. Al Jassar 《Journal of the Indian Society of Remote Sensing》2008,36(2):123-136
Spaceborne Imaging Radar (SIR-C) data acquired over Gujarat, India in 1994 were processed and analysed using differnet techniques
applicable to polarimetric SAR data such as polarization signatures, polarization index, decomposition of the signal and polarization
phase difference and limited groundtruth data. It has been observed that multi-frequency polarimetric data enhances the potential
of retrieving geo-physical parameters. The polarization signatures are found to vary with the nature of the target. Target
decomposition of the returned signal will be useful for the classification of various features. Polarization Phase Difference
(PPD) gives good information about the vegetation parameters. 相似文献
192.
Christoph Förste Roland Schmidt Richard Stubenvoll Frank Flechtner Ulrich Meyer Rolf König Hans Neumayer Richard Biancale Jean-Michel Lemoine Sean Bruinsma Sylvain Loyer Franz Barthelmes Saskia Esselborn 《Journal of Geodesy》2008,82(6):331-346
The recent improvements in the Gravity Recovery And Climate Experiment (GRACE) tracking data processing at GeoForschungsZentrum
Potsdam (GFZ) and Groupe de Recherche de Géodésie Spatiale (GRGS) Toulouse, the availability of newer surface gravity data
sets in the Arctic, Antarctica and North-America, and the availability of a new mean sea surface height model from altimetry
processing at GFZ gave rise to the generation of two new global gravity field models. The first, EIGEN-GL04S1, a satellite-only
model complete to degree and order 150 in terms of spherical harmonics, was derived by combination of the latest GFZ Potsdam
GRACE-only (EIGEN-GRACE04S) and GRGS Toulouse GRACE/LAGEOS (EIGEN-GL04S) mean field solutions. The second, EIGEN-GL04S1 was
combined with surface gravity data from altimetry over the oceans and gravimetry over the continents to derive a new high-resolution
global gravity field model called EIGEN-GL04C. This model is complete to degree and order 360 and thus resolves geoid and
gravity anomalies at half- wavelengths of 55 km at the equator. A degree-dependent combination method has been applied in
order to preserve the high accuracy from the GRACE satellite data in the lower frequency band of the geopotential and to form
a smooth transition to the high-frequency information coming from the surface data. Compared to pre-CHAMP global high-resolution
models, the accuracy was improved at a spatial resolution of 200 km (half-wavelength) by one order of magnitude to 3 cm in
terms of geoid heights. The accuracy of this model (i.e. the commission error) at its full spatial resolution is estimated
to be 15 cm. The model shows a reduced artificial meridional striping and an increased correlation of EIGEN-GL04C-derived
geostrophic meridional currents with World Ocean Atlas 2001 (WOA01) data. These improvements have led to select EIGEN-GL04C
for JASON-1 satellite altimeter data reprocessing.
Electronic Supplementary Material The online version of this article (doi:) contains supplementary material, which is available to authorized users. 相似文献
193.
The Bayesian detection of discontinuities in a polynomial regression and its application to the cycle-slip problem 总被引:4,自引:1,他引:3
Maria Clara de Lacy Mirko Reguzzoni Fernando Sansò Giovanna Venuti 《Journal of Geodesy》2008,82(9):527-542
This paper deals with the problem of detecting and correcting cycle-slips in Global Navigation Satellite System (GNSS) phase
data by exploiting the Bayesian theory. The method is here applied to undifferenced observations, because repairing cycle-slips
already at this stage could be a useful pre-processing tool, especially for a network of permanent GNSS stations. If a dual
frequency receiver is available, the cycle-slips can be easily detected by combining two phase observations or phase and range
observations from a single satellite to a single receiver. These combinations, expressed in a distance unit form, are completely
free from the geometry and depend only on the ionospheric effect, on the electronic biases and on the initial integer ambiguities;
since these terms are expected to be smooth in time, at least in a short period, a cycle-slip in one or both the two carriers
can be modelled as a discontinuity in a polynomial regression. The proposed method consists in applying the Bayesian theory
to compute the marginal posterior distribution of the discontinuity epoch and to detect it as a maximum a posteriori (MAP)
in a very accurate way. Concerning the cycle-slip correction, a couple of simultaneous integer slips in the two carriers is
chosen by maximazing the conditional posterior distribution of the discontinuity amplitude given the detected epoch. Numerical
experiments on simulated and real data show that the discontinuities with an amplitude 2 or 3 times larger than the noise
standard deviation are successfully identified. This means that the Bayesian approach is able to detect and correct cycle-slips
using undifferenced GNSS observations even if the slip occurs by one cycle. A comparison with the scientific software BERNESE
5.0 confirms the good performance of the proposed method, especially when data sampled at high frequency (e.g. every 1 s or
every 5 s) are available. 相似文献
194.
195.
196.
Lars E. Sjöberg 《Journal of Geodesy》2008,82(9):565-567
Through each of two known points on the ellipsoid a geodesic is passing in a known azimuth. We solve the problem of intersection
of the two geodesics. The solution for the latitude is obtained as a closed formula for the sphere plus a small correction,
of the order of the eccentricity of the ellipsoid, which is determined by numerical integration. The solution is iterative.
Once the latitude is obtained, the longitude is determined without iteration. 相似文献
197.
This article presents the application of a multivariate prediction technique for predicting universal time (UT1–UTC), length of day (LOD) and the axial component of atmospheric angular momentum (AAM χ 3). The multivariate predictions of LOD and UT1–UTC are generated by means of the combination of (1) least-squares (LS) extrapolation of models for annual, semiannual, 18.6-year, 9.3-year oscillations and for the linear trend, and (2) multivariate autoregressive (MAR) stochastic prediction of LS residuals (LS + MAR). The MAR technique enables the use of the AAM χ 3 time-series as the explanatory variable for the computation of LOD or UT1–UTC predictions. In order to evaluate the performance of this approach, two other prediction schemes are also applied: (1) LS extrapolation, (2) combination of LS extrapolation and univariate autoregressive (AR) prediction of LS residuals (LS + AR). The multivariate predictions of AAM χ 3 data, however, are computed as a combination of the extrapolation of the LS model for annual and semiannual oscillations and the LS + MAR. The AAM χ 3 predictions are also compared with LS extrapolation and LS + AR prediction. It is shown that the predictions of LOD and UT1–UTC based on LS + MAR taking into account the axial component of AAM are more accurate than the predictions of LOD and UT1–UTC based on LS extrapolation or on LS + AR. In particular, the UT1–UTC predictions based on LS + MAR during El Niño/La Niña events exhibit considerably smaller prediction errors than those calculated by means of LS or LS + AR. The AAM χ 3 time-series is predicted using LS + MAR with higher accuracy than applying LS extrapolation itself in the case of medium-term predictions (up to 100 days in the future). However, the predictions of AAM χ 3 reveal the best accuracy for LS + AR. 相似文献
198.
By using sonar imaging, this paper presents a new algorithm for the clustering of seabed types based on the self-organizing feature maps (SOFM) neural network. The theory as well as data processing is studied in detail. Some valuable conclusions and suggestions are given 相似文献
199.
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: |
200.
Kristine M. Larson Eric E. Small Ethan Gutmann Andria Bilich Penina Axelrad John Braun 《GPS Solutions》2008,12(3):173-177
Measurements of soil moisture are important for studies of climate and weather forecasting, flood prediction, and aquifer
recharge studies. Although soil moisture measurement networks exist, most are sparsely distributed and lack standardized instrumentation.
Measurements of soil moisture from satellites have extremely large spatial footprints (40–60 km). A methodology is described
here that uses existing networks of continuously-operating GPS receivers to measure soil moisture fluctuations. In this technique,
incoming signals are reflected off and attenuated by the ground before reception by the GPS receiver. These multipath reflections
directly affect signal-to-noise ratio (SNR) data routinely collected by GPS receivers, creating amplitude variations that
are a function of ground reflectivity and therefore soil moisture content. After describing this technique, multipath reflection
amplitudes at a GPS site in Tashkent, Uzbekistan are compared to estimates of soil moisture from the Noah land surface model.
Although the GPS multipath amplitudes and the land surface model are uncalibrated, over the 70-day period studied, they both
rise sharply following each rainfall event and slowly decrease over a period of ∼10 days. 相似文献