Prediction of earth rotation parameters based on improved weighted least squares and autoregressive model

In this paper, an improved weighted least squares （WLS）, together with autoregressive （AR） model, is proposed to improve prediction accuracy of earth rotation parameters（ERP）. Four weighting schemes are developed and the optimal power e for determination of the weight elements is studied. The results show that the improved WLS-AR model can improve the ERP prediction accuracy effectively, and for different prediction intervals of ERP, different weight scheme should be chosen.

Earth Rotation Parameter Estimation by GPS Observations

The methods of Earth rotation parameter (ERP) estimation based on IGS SINEX file of GPS solution are discussed in detail. There are two different ways to estimate ERP: one is the parameter transformation method, and the other is direct adjustment method with restrictive conditions. By comparing the estimated results with independent copyright program to IERS results, the residual systemic error can be found in estimated ERP with GPS observations.

Earth rotation parameter and variation during 2005—2010 solved with LAGEOS SLR data

Time series of Earth rotation parameters were estimated from range data measured by the satellite laser ranging technique to the Laser Geodynamics Satellites（LAGEOS）-1/2 through 2005 to 2010 using the dynamic method. Compared with Earth orientation parameter（EOP）C04, released by the International Earth Rotation and Reference Systems Service, the root mean square errors for the measured X and Y of polar motion（PM） and length of day（LOD）were 0.24 and 0.25 milliarcseconds（mas）, and 0.068 milliseconds（ms）, respectively.Compared with ILRSA EOP, the X and Y of PM and LOD were 0.27 and 0.30 mas, and 0.054 ms, respectively. The time series were analyzed using the wavelet transformation and least squares methods. Wavelet analysis showed obvious seasonal and interannual variations of LOD, and both annual and Chandler variations of PM; however, the annual variation could not be distinguished from the Chandler variation because the two frequencies were very close. The trends and periodic variations of LOD and PM were obtained in the least squares sense, and PM showed semi-annual, annual, and Chandler periods.Semi-annual, annual, and quasi-biennial cycles for LOD were also detected. The trend rates of PM in the X and Y directions were 3.17 and 1.60 mas per year, respectively, and the North Pole moved to 26.8E relative to the crust during 2005—2010. The trend rate of the LOD change was 0.028 ms per year.

Convex Optimization-Based Rotation Parameter Estimation Using Micro-Doppler

We present a novel algorithm that can determine rotation-related parameters of a target using FMCW （frequency modulated continuous wave） radars, not utilizing inertia information of the target. More specifically, the proposed algorithm estimates the angular velocity vector of a target as a function of time, as well as the distances of scattering points in the wing tip from the rotation axis, just by analyzing Doppler spectrograms obtained from three or more radars. The obtained parameter values will be useful to classify targets such as hostile warheads or missiles for real-time operation, or to analyze the trajectory of targets under test for the instrumentation radar operation. The proposed algorithm is based on the convex optimization to obtain the rotation-related parameters. The performance of the proposed algorithm is assessed through Monte Carlo simulations. Estimation performance of the proposed algorithm depends on the target and radar geometry and improves as the number of iterations of the convex optimization steps increases.

Rotational parameters estimation of maneuvering target in ISAR imaging

The rotational parameters estimation of maneuvering target is the key of cross-range scaling of ISAR （inverse synthetic aperture radar）, which can be used in the target feature extraction. The cross-range signal model of rotating target with fixed acceleration is presented and the weighted linear least squares estimation of rotational parameters with fixed velocity or acceleration is proposed via the relationship of cross-range FM （frequency modulation） parameter, scatterers coordinates and rotational parameters. The FM parameter is calculated via RWT （Radon-Wigner transform）. The ISAR imaging and cross-range scaling based on scaled RWT imaging method are implemented after obtaining rotational parameters. The rotational parameters estimation and cross-range scaling are validated by the ISAR processing of experimental radar data, and the method presents good application foreground to the ISAR imaging and scaling of maneuvering target.

A modified stochastic model for LS+AR hybrid method and its application in polar motion short-term prediction

Short-term(up to 30 days)predictions of Earth Rotation Parameters(ERPs)such as Polar Motion(PM:PMX and PMY)play an essential role in real-time applications related to high-precision reference frame conversion.Currently,least squares(LS)+auto-regressive(AR)hybrid method is one of the main techniques of PM prediction.Besides,the weighted LS+AR hybrid method performs well for PM short-term prediction.However,the corresponding covariance information of LS fitting residuals deserves further exploration in the AR model.In this study,we have derived a modified stochastic model for the LS+AR hybrid method,namely the weighted LS+weighted AR hybrid method.By using the PM data products of IERS EOP 14 C04,the numerical results indicate that for PM short-term forecasting,the proposed weighted LS+weighted AR hybrid method shows an advantage over both the LS+AR hybrid method and the weighted LS+AR hybrid method.Compared to the mean absolute errors(MAEs)of PMX/PMY sho rt-term prediction of the LS+AR hybrid method and the weighted LS+AR hybrid method,the weighted LS+weighted AR hybrid method shows average improvements of 6.61%/12.08%and 0.24%/11.65%,respectively.Besides,for the slopes of the linear regression lines fitted to the errors of each method,the growth of the prediction error of the proposed method is slower than that of the other two methods.

ISAR Imaging and Cross-Range Scaling Based on Image Rotation Correlation

With the rapid advancement of technology,not only do we need to acquire a clear in-verse synthetic aperture radar(ISAR)image,but also the real size of the target on the imaging plane,so it’s particularly important for the ISAR to rescale the images.That is,the ISAR image which is in the range-Doppler domain is converted into the range-azimuth domain.Actually,the key point to solving the problem is to estimate the rotation parameters.In this paper,a new scheme to rescale the images is proposed.For the sake of solving the problem of two-dimensional image blur and target high-speed,the instantaneous range instantaneous Doppler(IRID)method is used to obtain ISAR images,and the rotation parameters are estimated by comparing the rotation correlation of the two images.Using this method,the error of the estimated rotation parameters is greatly reduced,so that the target can be rescaled accurately.The simulation results verify the ef-fectiveness of the proposed algorithm.

Hyperon Effects on the Spin Parameter of Rotating Neutron Stars

Based on the equations of state from the relativistic mean field theory without and with the inclusion of strangeness-bearing hyperons, we study the dimensionless spin parameter j = cJ/（GM2） of uniformly rotat- ing neutron stars. It is shown that the maximum value of the spin parameter jmax of a neutron star rotating at the Keplerian frequency fK is .jmax - 0.7 when the star mass M 〉 0.SM⊙, which is sustained for various versions of equations of state without and with hyperons. The relationship between j and the scaled rotation frequency f /fK is found to be insensitive to the star mass or the adopted equation of state in the models without hyperons. However, the emergence of byperons in neutron stars will lead to an uncertainty of the spin parameter j, which in turn could generate a complexity in the theoretical study of the quasi-periodic oscillations observed in disk-accreting compact-star systems.

Determination of global geodetic parameters using satellite laser ranging to Galileo,GLONASS,and BeiDou satellites

The new Global Navigation Satellite System(GNSS)satellites,including GLONASS,Galileo,and BeiDou system,are equipped with Laser Retroreflector Arrays(LRA)to support Satellite Laser Ranging(SLR)tracking,which contributes to the estimation of global geodetic parameters.In this study,we estimate the global geodetic parameters using the SLR observations to GNSS satellites and also investigate the effects of different data processing strategies on the estimated Earth Rotation Parameters(ERP),geocenter motion,and terrestrial scale.The results indicate that setting range bias parameters for each satellite-station pair can effectively account for the satellite-specific biases induced by LRAs,leading to smaller Root Mean Square Errors(RMSE)of the post-fit SLR residuals.Furthermore,estimating the range biases for each satellite-station pair improves the accuracy of the estimated station coordinates and ERP.We also examine the impact of different arc lengths on the estimates of ERP,geocenter motion,and terrestrial scale.The results show that extending arc length can significantly reduce the formal error of ERP.The 7-day strategy produces the smallest RMSEs of 473 microarcseconds and 495 microarcseconds for the estimated X-and Y-component of pole coordinates,and 52 microseconds for length-of-day,respectively.However,the estimated geocenter motion is less affected by the arc length,even the shortest 1-day arc strategy can capture the seasonal variations of geocenter motion in Z component.For scale estimation,extending the arc length notably improves the accuracy of the estimated station coordinates and scale,but this advantage becomes less noticeable in longer arcs.The 7-day solution also obtains the closet scale results compared to ITRF2014,with the RMSE of 2.10×10^(–9).

A new polar motion prediction method combined with the difference between polar motion series

After the first Earth Orientation Parameters Prediction Comparison Campaign(1 st EOP PCC),the traditional method using least-squares extrapolation and autoregressive(LS+AR)models was considered as one of the polar motion prediction methods with higher accuracy.The traditional method predicts individual polar motion series separately,which has a single input data and limited improvement in prediction accuracy.To address this problem,this paper proposes a new method for predicting polar motion by combining the difference between polar motion series.The X,Y,and Y-X series were predicted separately using LS+AR models.Then,the new forecast value of X series is obtained by combining the forecast value of Y series with that of Y-X series;the new forecast value of Y series is obtained by combining the forecast value of X series with that of Y-X series.The hindcast experimental comparison results from January 1,2011 to April 4,2021 show that the new method achieves a maximum improvement of 12.95%and 14.96%over the traditional method in the X and Y directions,respectively.The new method has obvious advantages compared with the differential method.This study tests the stability and superiority of the new method and provides a new idea for the research of polar motion prediction.

The deforming and rotating Earth——A review of the 18th International Symposium on Geodynamics and Earth Tide,Trieste 2016

The 18th International Symposium on Geodynamics and Earth Tides 2016 covered phenomena that generate temporal variations in geodetic and geophysical observations. In calculating the stress field for Earth tides, the observed geodetic response is used for defining the Earth＇s theology, the Earth internal structure, ＇Earth rotation parameters, and the functioning of the sophisticated instrumentation mounted on Earth and satellites. The instrumentation capable of observing Earth tides, measures changes generated by lithospheric plate movements, as the earthquake cycle and volcanism. Hydrology, tem- perature, and pressure, either of natural or anthropogenic origin, affect the high precision observations, and therefore must be included in this study-realm.

Temporal-spatial subspaces modern combination method for 2D-DOA estimation in MIMO radar

A 2D-direction of arrival estimation (DOAE) for multi input and multi-output (MIMO) radar using improved multiple temporal-spatial subspaces in estimating signal parameters via rotational invariance techniques method (TS-ESPRIT) is introduced. In order to realize the improved TS-ESPRIT, the proposed algorithm divides the planar array into multiple uniform sub-planar arrays with common reference point to get a unified phase shifts measurement point for all sub-arrays. The TS-ESPRIT is applied to each sub-array separately, and in the same time with the others to realize the parallelly temporal and spatial processing, so that it reduces the non-linearity effect of model and decreases the computational time. Then, the time difference of arrival (TDOA) technique is applied to combine the multiple sub-arrays in order to form the improved TS-ESPRIT. It is found that the proposed method achieves high accuracy at a low signal to noise ratio (SNR) with low computational complexity, leading to enhancement of the estimators performance.

Low-complexity method for DOA estimation based on ESPRIT

A low-complexity method for direction of arrival（DOA） estimation based on estimation signal parameters via rotational invariance technique（ESPRIT） is proposed.Instead of using the cross-correlation vectors in multistage Wiener filter（MSWF）,the orthogonal residual vectors obtained in conjugate gradient（CG） method span the signal subspace used by ESPRIT.The computational complexity of the proposed method is significantly reduced,since the signal subspace estimation mainly needs two matrixvector complex multiplications at the iteration of data level.Furthermore,the prior training data are not needed in the proposed method.To overcome performance degradation at low signal to noise ratio（SNR）,the expanded signal subspace spanned by more basis vectors is used and simultaneously renders ESPRIT yield redundant DOAs,which can be excluded by performing ESPRIT once more using the unexpanded signal subspace.Compared with the traditional ESPRIT methods by MSWF and eigenvalue decomposition（EVD）,numerical results demonstrate the satisfactory performance of the proposed method.

High Resolution Multipath Time Delay Estimation Based on FLOCCS-ESPRIT

The non-Gaussian α-stable distribution is introduced to model impulsive noise. Based on the theory of fractional lower order statistics (FLOS), the fractional lower order cross-covariance (FLOCC) sequence for two received signals is obtained and the fractional lower order cross-covariance spectrum (FLOCCS) can be approached by taking a Fourier transform for the FLOCC sequence. When the FLOCCS is treated as a sequence in the time domain, the problem of multipath time delay estimation (TDE) may be converted into one on multi-frequencies estimation or directions of arrival estimation. Accordingly, the high resolution multipath TDE can be realized with the ESPRIT technology. This idea on multipath TDE is referred to as FLOCCS-ESPRIT in this paper. Computer simulations show that this method has good performance both in a Gaussian noise and in an impulsive noise environment.

MULTI-INVARIANCE ESPRIT-LIKE ALGORITHMS FOR COHERENT DOA ESTIMATION

Estimation of Signal Parameters via Rotational Invariance Technique(ESPRIT) algorithm can estimate Direction-Of-Arrival(DOA) of coherent signal,but its performance can not reach full satisfaction.We reconstruct the received signal to form data model with multi-invariance property,and multi-invariance ESPRIT algorithm for coherent DOA estimation is proposed in this paper.The proposed algorithm can resolve the DOAs of coherent signals and performs better in DOA estimation than that of ESPRIT-like algorithm.Meanwhile,it identifies more DOAs than ESPRIT-like algorithm.The simulation results demonstrate its validity.

SEQUENTIAL DIAGNOSIS FOR A CENTRIFUGAL PUMP BASED ON FUZZY NEURAL NETWORK

A sequential diagnosis method is proposed based on a fuzzy neural network realized by ＂the partially-linearized neural network （PNN）＂, by which the fault types of rotating machinery can be precisely and effectively distinguished at an early stage on the basis of the possibilities of symptom parameters. The non-dimensional symptom parameters in time domain are defined for reflecting the features of time signals measured for the fault diagnosis of rotating machinery. The synthetic detection index is also proposed to evaluate the sensitivity of non-dimensional symptom parameters for detecting faults. The practical example of condition diagnosis for detecting and distinguishing fault states of a centrifugal pump system, such as cavitation, impeller eccentricity which often occur in a centrifugal pump system, are shown to verify the efficiency of the method proposed in this paper.

COMPENSATION FOR THE MUTUAL COUPLING EFFECT FOR THE ESPRIT ALGORITHM IN SINGLE SNAPSHOT ARRAY PROCESSING

An effective method is introduced to compensate the effects of mutual coupling for the Estimation of Signal Parameter via Rotational Invariance Techniques (ESPRIT) direction finding algorithm in application of signal snapshot array processing.Changing the covariance matrix into a Teoplitz matrix can achieve high resolution in the Direction Of Arrive (DOA) estimation.How the mutual coupling affects the array antennas has been discussed and a new definition of mutual im- pedance has been used to characterize the mutual coupling effects between the array elements.Based on the new mutual impedance matrix,a practical method is presented to eliminate the effects of mutual coupling for ESPRIT in the single snapshot data processing.The simulation results show that, this new method not only properly reduces the effects of mutual coupling,but also maintains its steady performance even for weak signals.

Effect of Coriolis and centrifugal forces on flow and heat transfer at high rotation number and high density ratio in non orthogonally internal cooling channel

Numerical predictions of three-dimensional flow and heat transfer are performed for a two-pass square channel with 45° staggered ribs in non-orthogonally mode-rotation using the second moment closure model. At Reynolds number of 25,000, the rotation numbers studied were 0,0.24, 0.35 and 1.00. The density ratios were 0.13, 0.23 and 0.50. The results show that at high buoyancy parameter and high rotation number with a low density ratio, the flow in the first passage is governed by the secondary flow induced by the rotation whereas the secondary flow induced by the skewed ribs was almost distorted. As a result the heat transfer rate is enhanced on both co-trailing and co-leading sides compared to low and medium rotation number. In contrast, for the second passage, the rotation slightly reduces the heat transfer rate on co-leading side at high rotation number with a low density ratio and degrades it significantly on both co-trailing and co-leading sides at high buoyancy parameter compared to the stationary, low and medium rotation numbers. The numerical results are in fair agreement with available experimental data in the bend region and the second passage, while in the first passage were overestimated at low and medium rotation numbers.

GSTAR:an innovative software platform for processing space geodetic data at the observation level

To meet the demands for the data combination with multiple space geodetic techniques at the observation level,we developed a new software platform with high extensibility and computation efficiency,named space Geodetic SpatioTemporal data Analysis and Research software(GSTAR).Most of the modules in the GSTAR are coded in C++with object-oriented programming.The layered modular theory is adopted for the design of the software,and the antenna-based data architecture is proposed for users to construct personalized geodetic application scenarios easily.The initial performance of the GSTAR software is evaluated by processing the Global Navigation Satellite System(GNSS)data collected from 315 globally distributed stations over two and a half years.The accuracy of GNSS-based geodetic products is evaluated by comparing them with those released by International GNSS Service(IGS)Analysis Centers(AC).Taking the products released by European Space Agency(ESA)as reference,the Three-Dimension(3D)Root-Mean-Squares(RMS)of the orbit differences are 2.7/6.7/3.3/7.7/21.0 cm and the STandard Deviations(STD)of the clock differences are 19/48/16/32/25 ps for Global Positioning System(GPS),GLObal NAvigation Satellite System(GLONASS),Galileo navigation satellite system(Galileo),BeiDou Navigation Satellite System(BDS),Medium Earth Orbit(MEO),and BDS Inclined Geo-Synchronous Orbit(IGSO)satellites,respectively.The mean values of the X and Y components of the polar coordinate and the Length of Day(LOD)with respect to the International Earth Rotation and Reference Systems Service(IERS)14 C04 products are-17.6 microarc-second(μas),9.2μas,and 14.0μs/d.Compared to the IGS daily solution,the RMSs of the site position differences in the north/east/up direction are 1.6/1.5/3.9,3.8/2.4/7.6,2.5/2.4/7.9 and 2.7/2.3/7.4 mm for GPS-only,GLONASS-only,Galileo-only,and BDS-only solution,respectively.The RMSs of the differences of the tropospheric Zenith Path Delay(ZPD),the north gradients,and the east gradients are 5.8,0.9,and 0.9 mm with respect to the IGS products.The X and Y components of the geocenter motion estimated from GPS-only,Galileo-only,and BDS-only observations well agree with IGS products,while the Z component values are much nosier where anomalous harmonics in GNSS draconitic year can be found.The accuracies of the above products calculated by the GSTAR are comparable with those from different IGS ACs.Compared to the precise scientific orbit products,the 3D RMS of the orbit differences for the two Gravity Recovery and Climate Experiment Follow-on(GRACE-FO)satellites is below 1.5 cm by conducting Precise Point Positioning with Ambiguity Resolution(PPP-AR).In addition,a series of rapid data processing algorithms are developed,and the operation speed of the GSTAR software is 5.6 times faster than that of the Positioning and Navigation Data Analyst(PANDA)software for the quad-system precise orbit determination procedure.

Angle Estimation in Monostatic MIMO Radar with Low-Complexity Beamspace Unitary ESPRIT

A low-complexity angle estimation method for multiple-input multiple-output(MIMO) radar using beamspace unitary estimation of signal parameters via rotational invariance techniques(ESPRIT) is presented.Reduced-dimensional transformation is firstly utilized as a pre-processing to obtain the reduced-dimensional data matrix, and then a conjugate centrosymmetric discrete Fourier transform(DFT) matrix is employed to map the received data into lower-dimensional beamspace and transforms the complex covariance matrix into a realvalued one. At last, the rotational invariance structure of the real-valued signal subspace is constructed in the beamspace to obtain the estimation of direction of arrival(DOA). Compared with the other ESPRIT algorithms,the proposed method can achieve improved estimation performance with a significantly reduced computational complexity. Simulation results are presented to demonstrate the effectiveness of the proposed method.