Methodology for local correction of the heights of global geoid models to improve the accuracy of GNSS leveling

At present,one of the methods used to determine the height of points on the Earth’s surface is Global Navigation Satellite System(GNSS)leveling.It is possible to determine the orthometric or normal height by this method only if there is a geoid or quasi-geoid height model available.This paper proposes the methodology for local correction of the heights of high-order global geoid models such as EGM08,EIGEN-6C4,GECO,and XGM2019e_2159.This methodology was tested in different areas of the research field,covering various relief forms.The dependence of the change in corrected height accuracy on the input data was analyzed,and the correction was also conducted for model heights in three tidal systems:"tide free","mean tide",and"zero tide".The results show that the heights of EIGEN-6C4 model can be corrected with an accuracy of up to 1 cm for flat and foothill terrains with the dimensionality of 1°×1°,2°×2°,and 3°×3°.The EGM08 model presents an almost identical result.The EIGEN-6C4 model is best suited for mountainous relief and provides an accuracy of 1.5 cm on the 1°×1°area.The height correction accuracy of GECO and XGM2019e_2159 models is slightly poor,which has fuzziness in terms of numerical fluctuation.

Evaluation of atmospheric corrections on hyperspectral data with special reference to mineral mapping

Hyperspectral images have wide applications in the fields of geology,mineral exploration,agriculture,forestry and environmental studies etc.due to their narrow band width with numerous channels.However,these images commonly suffer from atmospheric effects,thereby limiting their use.In such a situation,atmospheric correction becomes a necessary pre-requisite for any further processing and accurate interpretation of spectra of different surface materials/objects.In the present study,two very advance atmospheric approaches i.e.QUAC and FLAASH have been applied on the hyperspectral remote sensing imagery.The spectra of vegetation,man-made structure and different minerals from the Gadag area of Karnataka,were extracted from the raw image and also from the QUAC and FLAASH corrected images.These spectra were compared among themselves and also with the existing USGS and JHU spectral library.FLAASH is rigorous atmospheric algorithm and requires various parameters to perform but it has capability to compensate the effects of atmospheric absorption.These absorption curves in any spectra play an important role in identification of the compositions.Therefore,the presence of unwanted absorption features can lead to wrong interpretation and identification of mineral composition.FLAASH also has an advantage of spectral polishing which provides smooth spectral curves which helps in accurate identification of composition of minerals.Therefore,this study recommends that FLAASH is better than QUAC for atmospheric correction and correct interpretation and identification of composition of any object or minerals.

Data correction of the force balanced accelerometer

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Effects of tube system and data correction for fluctuating pressure test in wind tunnel

The accuracy of fluctuating pressure test in wind tunnel is affected by the tube system. By employing contradistinctive experimental method, systematic study was conducted to investigate the effects of the tube system on fluctuating pressure. The analyzed tube system parameters include tube length, inside diameter, curvature, deflection angle, thickness, material, restrictor length,restrictor inside diameter, and restrictor place. It is found that all the tube system parameters mentioned above except tube curvature have non-negligible effects on fluctuating pressure. Based on the research results, test methods were presented for the fluctuating pressure measurement in low-speed wind tunnel, which can obviously improve the data accuracy but not lose test efficiency. The effectiveness of the method is verified by the wind tunnel test.

Online Pattern Recognition and Data Correction of PMU Data Under GPS Spoofing Attack

Smart grids are increasingly dependent on data with the rapid development of communication and measurement.As one of the important data sources of smart grids,phasor measurement unit(PMU)is facing the high risk from attacks.Compared with cyber attacks,global position system(GPS)spoofing attacks(GSAs)are easier to implement because they can be exploited by portable devices,without the need to access the physical system.Therefore,this paper proposes a novel method for pattern recognition of GSA and an additional function of the proposed method is the data correction to the phase angle difference(PAD)deviation.Specifically,this paper analyzes the effect of GSA on PMU measurement and gives two common patterns of GSA,i.e.,the step attack and the ramp attack.Then,the method of estimating the PAD deviation across a transmission line introduced by GSA is proposed,which does not require the line parameters.After obtaining the estimated PAD deviations,the pattern of GSA can be recognized by hypothesis tests and correlation coefficients according to the statistical characteristics of the estimated PAD deviations.Finally,with the case studies,the effectiveness of the proposed method is demonstrated,and the success rate of the pattern recognition and the online performance of the proposed method are analyzed.

An improved oil recovery prediction method for volatile oil reservoirs

To describe the complex phase transformation in the process of depletion exploitation of volatile oil reservoir,four fluid phases are defined,and production and remaining volume of these phases are calculated based on the principle of surface volume balance,then the recovery prediction method of volatile oil reservoir considering the influence of condensate content in released solution gas and the correction method of multiple degassing experiments data are established.Taking three typical kinds of crude oil(black oil,medium-weak volatile oil,strong volatile oil)as examples,the new improved method is used to simulate constant volume depletion experiments based on the corrected data of multiple degassing experiment to verify the reliability of the modified method.By using"experimental data and traditional method","corrected data and traditional method"and"corrected data and modified method",recovery factors of these three typical kinds of oil are calculated respectively.The source of parameters and the calculation methods have little effect on the recovery of typical black oil.However,with the increase of crude oil volatility,the oil recovery will be seriously underestimated by using experimental data or traditional method.The combination of"corrected data and modified method"considers the influence of condensate in gas phase in both experimental parameters and calculation method,and has good applicability to typical black oil and volatile oil.The strong shrinkage of volatile oil makes more"liquid oil"convert to"gaseous oil",so volatile oil reservoir can reach very high oil recovery by depletion drive.

Imaging Algorithms for Cosmic Ray Muon Radiography Detection of Nuclear Materials

Cosmic ray muon radiography which has good penetration ability and is sensitive to high-Z materials, is an effective method to detect shielded nuclear materials. This paper summarizes methods developed to process muon radiography in Tsinghua University. The methods include detector data correction, reconstruction algorithms （maximum likelihood scattering, MLS, and the maximum likelihood scattering and displacement, MLSD） acceleration, and the modification of the normalized mean absolute distance measure （NMADM） into a picture comparison binarization method （PCBM） which is more suitable for cosmic ray muon radiographs. Simulations demonstrate that all these methods give excellent results, so that cosmic muon radiography can become more widely used.