Dual Crossover Research Articles

The application of least-square collocation and variance component estimation in crossover analysis of satellite altimetry observations and altimeter calibration

ABSTRACT In this study, the collocation method accompanied with variance component estimation is used for least square adjustment of crossover observations in order to determine the effects of radial errors on the observations of satellite altimetry. The collocation is used for time series analysis of sea surface height observations both for predicting the possible missing observations in each cycle, and for approximating the observation of each cycle at crossover points. In addition, use is made of the variance component estimation to quantify the noise variance of observations and improve the least square evaluation of radial errors. For analysis of radial errors, two different approaches are followed, in the first approach, the radial errors are assumed to behave like a series of trigonometric function, the coefficients of which are unknowns which should be determined from observations. In the second approach, the values of radial errors, for ascending and descending passes are determined. Our results show the efficiency of collocation algorithm for highly accurate time series analysis of altimetry observations and moreover, they reveal the effectiveness of variance component estimation for true noise specification of observations which can significantly improve the results of least square adjustment. The outcome of this study can be used to calibration of altimeters. The numerical results indicate that the mean range biases of Topex/Poseidon, Jason 1-2 and ENVISAT in the six single and dual crossover points using the first and the second methods are about 0, 84, 33, 204 and 0, 98, 41, 286 mm, respectively.

Improvement of Sea Surface Height Measurements of HY-2A Satellite Altimeter Using Jason-2

HY-2A, which was launched on 16 August 2011, is the Chinese first microwave ocean dynamics environment satellite. Analyses of HY-2A daily sea-level anomaly data and HY-2A–Jason-2 (H-J) dual crossover sea-level anomaly differences show that HY-2A has measurement differences that mainly refer to an orbit error. H-J crossover differences and HY-2A–HY-2A (H-H) crossover differences give an estimate of the HY-2A orbit error. Smoothing cubic-spline functions are then used to obtain a continuous estimation of the HY-2A orbit error over time. On the basis of the simultaneous global minimization of H-J dual crossover differences and H-H crossover differences, the HY-2A observation error is efficiently reduced and height measurement data that are more precise are obtained. Specifically, the range bias/trend of the HY-2A altimeter is removed effectively and the root mean square of H-J crossover sea-level anomaly differences decrease from above 60 cm to 5.64 cm, and the standard deviation of H-J crossover differences decreases from 6.68 to 5.64 cm. Furthermore, the rms and standard deviations of H-H crossover differences both decrease from 7.46 to 6.55 cm. The results show that HY-2A after correction has a measurement accuracy and precision that are comparable to those of Jason-2.

A Knowledge Rule Mining Method for the Evaluation of Bilingual Teaching Quality in Universities Based on Genetic Algorithm

Bilingual teaching is the inevitable reform and development trend of higher education, and it is a very important job for us to evaluate the bilingual teaching quality. Currently, we do not have an effective evaluation system for bilingual teaching quality. In this study, the factors which affect bilingual teaching quality are analyzed and the evaluation index system of bilingual teaching quality in universities is established firstly. Then, a knowledge rule mining method for the evaluation of bilingual teaching quality in universities based on an improved genetic algorithm is proposed. In the algorithm, selection operator, dual crossover operator and dual mutation operator are used to generate new knowledge rules. Knowledge rules are evaluated by their accuracy, coverage and reliability. Experimental results show that this knowledge rule mining method is feasible and valid.

Energy Efficient Genetic Coding Algorithm in Multimedia Sensor Network

Since the random deployment of wireless multimedia sensor networks and excessive energy consumption, which is caused by hardware resource constraints, affect the network life cycle and other issues, this paper proposes the energy efficient network of genetic coding algorithm. The algorithm takes the maximum running rounds of network nodes and maximum deployment as the basis to establish the initial individual, adopt dual crossover and optimal genome mutagenesis to complete inter-individual crossover and mutation. Experimental results show that: the proposed algorithm balances the energy consumption of each node in the network and thus prolong the network lifetime.

A Knowledge Rule Mining Method for the Evaluation of Library Readers Satisfaction Rate

The readers satisfaction rate is an important index of library service quality. Evaluation of library readers satisfaction rate depends on knowledge rules to a large extent. In this study, the synthesized evaluation index system of readers satisfaction rate was established firstly. Then, a method for mining the evaluation knowledge rules of readers satisfaction rate based on an improved genetic algorithm was proposed. In the algorithm, new knowledge rules were generated by selection operator, dual crossover operator and dual mutation operator. Knowledge rules were evaluated by their accuracy, coverage and reliability, and they were evaluated by linear combination method. Experimental results show that this method for mining knowledge rules is valid. It is helpful for us to evaluate library readers satisfaction rate fairly and objectively.

Evolutionary Cellular Automata Algorithm with Hybrid Discrete Variables and its Application to Mechanical Optimization

The optimization design about hybrid discrete variables synthesizing integer, discrete and continuous variables is very significant but also difficult in engineering, mathematics for programming and operational research. Aimed at shortages of existing optimum methods, in this paper, Evolutionary Cellar Automata Algorithm (ECAA) is proposed to complex optimization problem with hybrid discrete variables which has a digging operator and two learning operators (dual arithmetic crossover operator and chaos-peak-jumping operator). The computing examples of mechanical optimization design show that this algorithm has no special requirements on the characteristics of optimal designing problems, it has a fairly good universal adaptability and a reliable operation of program with a strong ability of overall convergence and high efficiency.

Cross-calibration of TOPEX/Poseidon, ERS-2 and GEOSAT altimetry

Long-term monitoring of the NASA (TOPEX) altimeter bias drift onboard TOPEX/Poseidon has been undertaken by comparison against in-situ tide gauge data and used as a benchmark for cross-calibration of the concurrent altimeter mission ERS-2 and of the earlier GEOSAT mission. Dual crossovers between ERS-2 and TOPEX/Poseidon provide a measure of the relative bias along with other parameters defining differences between the altimetric data sets. Attempts to link GEOSAT with the missions in the 1990s have relied on tide gauge time series with the assumption that geographically correlated errors in GEOSAT have zero effect. In this study we utilise GEOSAT crossovers and tide gauge enhanced altimetry between TOPEX/Poseidon and GEOSAT to estimate a 1 cy/rev correction simultaneously with the relative altimeter bias. Evidence of improvement is shown by comparison of the GEOSAT altimetry against the EGM96 mean sea-level.

The ERS-2 altimetric bias and gravity field enhancement using dual crossovers between ERS and TOPEX/Poseidon

Dual satellite crossovers (DXO) between the two European Remote Sensing satellites ERS-1 and ERS-2 and TOPEX/Poseidon are used to (1) refine the Earth's gravity field and (2) extend the study of the ERS-2 altimetric range stability to cover the first four years of its operation. The enhanced gravity field model, AGM-98, is validated by several methodologies and will be shown to provide, in particular, low geographically correlated orbital error for ERS-2. For the ERS-2 altimetric range study, TOPEX/Poseidon is first calibrated through comparison against in situ tide gauge data. A time series of the ERS-2 altimeter bias has been recovered along with other geophysical correction terms using tables for bias jumps in the range measurements at the single point target response (SPTR) events. On utilising the original version of the SPTR tables the overall bias drift is seen to be 2.6±1.0 mm/yr with an RMS of fit of 12.2 mm but with discontinuities at the centimetre level at the SPTR events. On utilising the recently released revised tables, SPTR2000, the drift is better defined at 2.4±0.6 mm/yr with the RMS of fit reduced to 3.7 mm. Investigations identify the sea-state bias as a source of error with corrections affecting the overall drift by close to 1.2 mm/yr.

A spectral optimally interpolated mean sea surface from satellite radar altimetry

A technique is presented for the development of a high-precision and high-resolution mean sea surface model utilising radar altimetric sea surface heights extracted from the geodetic phase of the European Space Agency (ESA) ERS-1 mission. The methodology uses a cubic-spline fit of dual ERS-1 and TOPEX crossovers for the minimisation of radial orbit error. Fourier domain processing techniques are used for spectral optimal interpolation of the mean sea surface in order to reduce residual errors within the initial model. The EGM96 gravity field and sea surface topography models are used as reference fields as part of the determination of spectral components required for the optimal interpolation algorithm. A comparison between the final model and 10 cycles of TOPEX sea surface heights shows differences of between 12.3 and 13.8 cm root mean square (RMS). An un-optimally interpolated surface comparison with TOPEX data gave differences of between 15.7 and 16.2 cm RMS. The methodology results in an approximately 10-cm improvement in accuracy. Further improvement will be attained with the inclusion of stacked altimetry from both current and future missions.

Analysis and representation of regional sea-level variability from altimetry and atmospheric-oceanic data

SUMMARY A simple representation of the sea-level variability in time at low and medium frequencies and at large and medium spatial scales is investigated that accounts for the correlation between sea-level heights and other atmospheric and oceanic parameters. The selected fields are sea-level height, sea-surface temperature, wind speed and sea-surface atmospheric pressure; they are considered in the interval between 1992 and 1997. The sea-level height data correspond to a single space altimetry mission (Topex/Poseidon) and provide a homogeneous data set. The dominant characteristics of the variability of each field and the coupled variability between two fields are analysed in the European seas using the spectral analysis method and the statistical methods of principal component analysis and canonical correlation analysis. In the single-field study, both the spectral and the principal component analyses show different characteristics of the sea-level height variability in the three seas. The strongest annual and semi-annual signals are in the Mediterranean Sea, whereas in the other two seas, especially in the Baltic Sea, the dominant spectral components have comparable power. The trends are interpreted as interannual variability due to the shortness of the investigated time interval. The highest positive trends are observed in the eastern Mediterranean Sea. In the coupled-fields study, both the linear regression analysis and the canonical correlation analysis show a high correlation between the sea-level height and the sea-surface temperature in the Mediterranean Sea and between the sea-level height and the wind speed in the North Sea and the Baltic Sea. The Mediterranean Sea is particularly suitable for building sea-level height models from the statistical methods because the first four modes of both the single- and the coupled-fields models account for about 90 per cent of the variance of the sea-level height field. It is therefore chosen as a test area to check the accuracy of the models and the ability of the canonical correlation method to predict the sea-level variability. The accuracy of the statistical models is assessed by computing dual crossover height differences between the Topex/Poseidon and ERS-1 and ERS-2 sea-surface heights corrected using the variability models. Both the single- and the coupled-fields models are found to be a good representation of the sea-level variability in the Mediterranean Sea, whereas the extrapolated canonical correlation model, derived using the sea-surface temperature as a predictor, is less accurate, but still acceptable. Relative bias and drift between the Topex/Poseidon and ERS data result from the analysis and reflect a non-homogeneous pre-processing of the altimetry data. The single-mission sea-level variability models are a first step towards the construction of a multimission sea-level model from unified multimission altimetry data.

Inferences from dual crossover analyses between concurrent satellite missions

Dual satellite crossovers or repeat pass data between different altimetric satellite missions provides a mechanism for resolution of constant and geographically correlated errors which are unobservable in single satellite crossovers. Through long-term analyses it is possible to characterise the form of the difference both temporally and spatially. In this study dual crossovers between TOPEX/Poseidon and the less accurate ERS datasets are analysed for errors in ERS with particular emphasis on the long-term stability of the altimetric datasets. Corresponding results are also presented from analysis of the ERS repeat pass data during the tandem period.

Accuracy assessment and refinement of the JGM-2 and JGM-3 gravity fields for radial positioning of ERS-1

ERS-1 radial positioning using the JGM-2 and JGM-3 gravity fields is assessed by analysing dual crossovers with TOPEX/Poseidon, neither field containing ERS-1 data. This method allows a more complete recovery of ERS-1 radial orbit error, specifically of the previously unattainable mean geographical error. The global analysis shows that the theoretical error derived from the JGM-2 covariance matrix is realistic and that JGM-3 represents a slight improvement, at least at the inclination of ERS-1. A latitudinal-based study in the southern ocean indicates possible weaknesses in both fields, notably for low and resonant geopotential orders m. A refinement of JGM-2, RGM-2, is undertaken through inclusion of ERS-1 and STELLA laser tracking and ERS-1 altimetry, reducing several of its deficiencies.

Comparison of gravity field modelling for ERS-1 using dual crossover constraint equations

Dual crossovers between TOPEX/Poseidon and ERS-1 provide a measure of the radial accuracy of ERS-1 relative to the more precise TOPEX/Poseidon orbits. In particular harmonic analysis of the residuals from narrow latitudinal bands yields the amplitude and phase of radial orbit error at specific orders in the Earth's gravity field. The procedure results in lumped harmonics of given orders which can be used either to refine a gravity field or to assess its accuracy. In this study the lumped harmonics will be employed to compare gravity fields in common use for ERS-1 and ERS-2 orbit determinations. Results will be presented from both the 35- and 168-day repeat cycles of ERS-1.

Effects of Alprazolam on Complex Human Functioning1

Benzodiazepines can reduce anxiety, can have favorable effects upon sleep, and may diminish problems that interfere with patients' quality of life. On the other hand, these drugs can generate transient anterograde amnesia and may diminish aspects of task performance. Research on the impact of alprazolam and other “tranquilizing” drugs has generally focused on tasks that remain below the complex efforts of managerial or professional personnel. Alprazolam‐induced reduction of anxiety under challenging conditions might aid complex task performance, yet anterograde amnesia might interfere. In the present research, managers participated in validated complex simulation tasks. In a double‐blind, dual crossover design, placebo, 0.5 mg, or 1.0 mg alprazolam was administered on 2 occasions during the task day. Drug treatment diminished performance on measures that require sequential actions but improved performance on measures less subject to short term memory but more determined by long‐term style of functioning. Thus, depending on task requirements, positive or negative alteration of performance might occur.

Analysis of global ERS‐1 altimetry by optimal Fourier transform interpolation

Optimal interpolation in the spatial domain is limited by computer storage requirements and the computational effort to invert the autocovariance matrix. The procedure can be simplified by use of the fast Fourier transform (FFT), where matrix inversion is replaced by a quotient of power spectral density (PSD) functions in the spectral domain. Such a methodology is developed and utilized to estimate an altimetric mean sea surface from a single 35‐day cycle of ERS‐1. ERS‐1 radial orbit error is first reduced by minimizing dual crossover residuals with TOPEXIPoseidon through solution for a sinusoidal correction for each ascending and descending arc along with the relative altimeter bias. A regular grid for ascending (descending) arcs is then formed by use of the equator‐crossing longitudes and the along‐track displacement. Gaps in the altimeter data set are filled by use of a reference model. PSDs derived from the data and reference surface enable computation of the least‐Squares estimator in the spectral do...

ERS-1 radial position refinement by dual crossover analysis with TOPEX/Poseidon

Achieving orbital accuracies in the radial direction for ERS-1 commensurate with those for TOPEX/Poseidon is of utmost importance for the integration of the two altimeter data sets. This paper outlines a procedure whereby the radial orbit error for ERS-1 is recovered as a time series expansion in the form of a finite Fourier series with additional terms for atmospheric drag, solar radiation pressure, and initial state vector mismodelling. Using a least squares collocation method with constraints derived from the JGM2 gravity field co-variance matrix, the radial error is recovered using both dual crossovers and ERS-1 single satellite crossovers. Aggregate arcs are then used to derive the ERS-1 orbit error over the repeat period of 35 days. The results are presented in the improvement of fit in the dual crossover, ERS-1 crossover and altimetry data sets as well as the recovery of an altimeter bias for the two satellites.

Accuracy assessment of TOPEX/Poseidon dual crossover correction of ERS-1 altimetry

Because of its greater altitude, the orbit of TOPEX/Poseidon (T/P) can be estimated to a superior accuracy to that of ERS-1. This fact can be used to reduce the radial orbit error contamination of ERS-1 altimetry through minimisation of dual crossover residuals between altimetry from the two satellites. By use of a sinusoidal orbit error approximation over arc lengths of half a circumnavigation, the dual crossover dataset has been used to refine ERS-1 radial positioning. This study has investigated the absorption into ERS-1 altimetry of geographically and temporally correlated T/P errors, particularly radial orbit errors. By modelling the periodic and geographically correlated T/P errors, some absorption of terms, including amplification of several periodic components has been demonstrated. This aliasing is influenced by the spatial and temporal sampling patterns associated with each arc, leading to highly geographically correlated absorption of T/P radial orbit errors, typically of the order of 50% of the total cumulative T/P radial orbit error.

Precise orbit determination and sea-surface topography from ERS-1

Results of ERS - 1 orbit refinement procedures for long-arcs are summarised with particular reference to gravity field modelling and sea-surface topography. Long arcs from the three day and thirty - five day repeat cycles have been used to refine the earth's gravity field constrained by the JGM- 2 covariance matrix and simultaneously to solve for the quasi - stationary sea - surface topography. Orbital computations are presented for arcs not included within the refinement process with improvements identified through rms of fit to laser, altimeter and single satellite crossover data. Additional results utilising dual crossovers with TOPEX / POSEIDON in a full dynamic process are also presented. In particular, reference is made to the relative altimeter biases between the respective satellites and the characteristics of the orbital adjustment through inclusion of dual crossover data.

Orbital refinement of ERS-1 using dual crossover arc techniques with TOPEX/POSEIDON

Orbital refinement of ERS-1 using dual crossover arc techniques with TOPEX/POSEIDON