The estimation of glacier flow velocity on a short-term scale is very important for further glacier dynamics research.In this study,10 Sentinel-1 ascending images and 10 Sentinel-1 descending images of Urumqi Glacier ...The estimation of glacier flow velocity on a short-term scale is very important for further glacier dynamics research.In this study,10 Sentinel-1 ascending images and 10 Sentinel-1 descending images of Urumqi Glacier No.1 in 2017 were used to calculate the glacier flow velocity in a high coherence period by DIn SAR technology and MAI technology,while the offset tracking technology was used to estimate the glacier flow velocity in a low coherence period.Then,the monthly three-dimensional flow velocity of the glacier was calculated by the Helmert variance component estimation method.Finally,the accuracy of the estimated glacier flow velocity on a monthly scale was evaluated.The results showed that:(1)the monthly scale motion velocity of Urumqi Glacier No.1 in May,June,July,and August 2017 was 0.273 m/month,0.657 m/month,0.582 m/month,and 0.392 m/month,respectively.(2)The accuracy of glacier surface velocity from May 2017 to August 2017 was 0.033 m/month,0.026 m/month,0.034 m/month and 0.037 m/month,respectively.(3)The accuracy of glacier surface flow velocity from May 2017 to August 2017 was 0.018 m/month,0.031 m/month,0.029 m/month and 0.030 m/month,respectively.Therefore,the research methodology based on the Sentinel-1 ascending and descending data and presented in this paper was applicable to the estimation of monthly-scale flow velocity of mountain glaciers.展开更多
In recent years,the development of domestic commercial synthetic aperture radar(SAR)is in full swing,with multiple commercial SAR satellites in orbit,showing great potential in disaster monitoring,natural resource man...In recent years,the development of domestic commercial synthetic aperture radar(SAR)is in full swing,with multiple commercial SAR satellites in orbit,showing great potential in disaster monitoring,natural resource management and deformation observation.Fucheng-1 is the first C-band commercial SAR satellite for interferometric SAR(InSAR)service developed by Spacety China,which marks the gradual maturity of China’s remote sensing data service.Based on the raw data collected by Fucheng-1,this paper firstly introduces the range-Doppler algorithm(RDA),then illustrates the parameter estimation method on the basis of fractional Fourier transform(FrFT)to realize the accurate estimation of azimuth chirp rate,which effectively improves imaging quality.Finally,the L1-norm regularization based sparse imaging method is utilized to reconstruct images from down-sampled data.Experimental results show that the sparse imaging algorithm can accurately reconstruct the down-sampled Fucheng-1 data and suppress sidelobes and clutter.展开更多
The Euler angle estimation is a calibration method for vector data measured by the magnetometer on a satellite.It is used to find the relative rotation between the coordinate system of the magnetometer and the satelli...The Euler angle estimation is a calibration method for vector data measured by the magnetometer on a satellite.It is used to find the relative rotation between the coordinate system of the magnetometer and the satellite(usually determined by Star Imagers).Before launch of the low-orbit,low-inclination Macao Science Satellite-1(known as MSS-1),we simulated the estimation of Euler angles by using the magnetic measurements of the in-orbit Swarm and China Seismo-Electromagnetic Satellite(noted as CSES),with various data combinations.In this study,11 data sets were designed to analyze the estimation results for the MSS-1 orbit by using a joint estimation method of the geomagnetic field model parameters and Euler angles.For the model results,we found that all the spatial power spectral lines showed behavior consistent with that of the CHAOS-7.8 model at low degrees(corresponding to large-scale magnetic signals).The spectra of models without global data coverage deviated much more(by a maximum of~10^(4) nT^(2))from those of the CHAOS-7.8 model at higher degrees.For models with global data coverage and with various data combinations,the spectral lines were distributed similarly.Moreover,the models with accordant power spectral distributions demonstrated different Euler angle estimations.As more vector data at higher latitudes were included,the estimated Euler angles varied monotonically in all three directions.The models with vector data in the same latitude range showed similar Euler angle results,regardless of whether the poleward scalar data were included.The largest value difference was found between the models using vector data within±40°latitudes and those using vector data within±60°latitudes,which reached to~28″.Therefore,we concluded that the inversion of the spherical harmonic Gauss coefficients in our tests was mainly affected by the spatial coverage range of the data,whereas the estimation of Euler angles largely depended on the latitude range where the vector data could be obtained.These results can be used for future in-flight data testing.We expect the estimation of Euler angles to improve as other methods are adopted.展开更多
Obtaining the spatial distribution of snow cover in mountainous areas using the optical image of remote sensing technology is difficult because of cloud and fog. In this study, the object-based principle component ana...Obtaining the spatial distribution of snow cover in mountainous areas using the optical image of remote sensing technology is difficult because of cloud and fog. In this study, the object-based principle component analysis–support vector machine(PCA–SVM) method is proposed for snow cover mapping through the integration of moderateresolution imaging spectroradiometer(MODIS) snow cover products and the Sentinel-1 synthetic aperture radar(SAR) scattering characteristics. First, derived from the Sentinel-1 A SAR images, the feature parameters, including VV/VH backscatter, scattering entropy, and scattering alpha, were used to describe the variations of snow and non-snow covers. Second, the optimum feature combinations of snow cover were formed from the feature parameters using the principle component analysis(PCA) algorithm. Finally, using the optimum feature combinations, a snow cover map with a 20 m spatial resolution was extracted by means of an object-based SVM classifier. This method was applied in the study area of the Xinyuan County, which is located in the western part of the Tianshan Mountains in Xinjiang, China. The accuracies in this method were analyzed according to the data observed at different experimental sites. Results showed that the snow cover pixels of the extraction were less than those in the actual situation(FB1=93.86, FB2=59.78). The evaluation of the threat score(TS), probability of detection(POD), and false alarm ratio(FAR) for the snow-covered pixels obtained from the two-stage SAR images were different(TS1=86.84, POD1=90.10, FAR1=4.01;TS2=56.40, POD2=57.62, FAR2=3.62). False and misclassifications of the snow cover and non-snow cover pixels were found. Although the classifications were not highly accurate, the approach showed potential for integrating different sources to retrieve the spatial distribution of snow covers during a stable period.展开更多
With a low resolution 1-bit ADC on its receiver(RX) side, MIMO with 1-bit ADC took a considerable step in the fulfillment of the hardware complexity constrains of the internet of things(IoT) PHY layer design. However,...With a low resolution 1-bit ADC on its receiver(RX) side, MIMO with 1-bit ADC took a considerable step in the fulfillment of the hardware complexity constrains of the internet of things(IoT) PHY layer design. However, applying 1-bit ADC at MIMO RX results in severe nonlinear quantization error. By which, almost all received signal amplitude information is completely distorted. Thus, MIMO channel estimation is considered as a major barrier towards practical realization of 1-bit ADC MIMO system. In this paper, two efficient sparsity-based channel estimation techniques are proposed for 1-bit ADC MIMO systems, namely the low complexity sparsity-based channel estimation(LCSCE), and the iterative adaptive sparsity channel estimation(IASCE). In these techniques, the sparsity of the 1-bit ADC MIMO channel is exploited to propose a new adaptive and iterative compressive sensing(CS) recovery algorithm to handle the 1-bit ADC quantization effect. The proposed algorithms are tested with the state-of-the-art 1-bit ADC MIMO constant envelope modulation(MIMO-CEM). The 1-bit ADC MIMO-CEM system is chosen as it fulfills both energy and hardware complexity constraints of the IoT PHY layer. Simulation results reveal the high effectiveness of the proposed algorithms in terms of spectral efficiency(SE) and computational complexity. The proposed LCSCE reduces the computational complexity of the 1-bit ADC MIMO-CEM channel estimation by 86%, while the IASCE reduces it by 96% compared to the recent techniques of MIMO-CEM channel estimation. Moreover, the proposed LCSCE and IASCE improve the spectrum efficiency by 76 % and 73 %, respectively, compared to the recent techniques.展开更多
A joint two-dimensional(2D)direction-of-arrival(DOA)and radial Doppler frequency estimation method for the L-shaped array is proposed in this paper based on the compressive sensing(CS)framework.Revised from the conven...A joint two-dimensional(2D)direction-of-arrival(DOA)and radial Doppler frequency estimation method for the L-shaped array is proposed in this paper based on the compressive sensing(CS)framework.Revised from the conventional CS-based methods where the joint spatial-temporal parameters are characterized in one large scale matrix,three smaller scale matrices with independent azimuth,elevation and Doppler frequency are introduced adopting a separable observation model.Afterwards,the estimation is achieved by L1-norm minimization and the Bayesian CS algorithm.In addition,under the L-shaped array topology,the azimuth and elevation are separated yet coupled to the same radial Doppler frequency.Hence,the pair matching problem is solved with the aid of the radial Doppler frequency.Finally,numerical simulations corroborate the feasibility and validity of the proposed algorithm.展开更多
We theoretically study the quantum Fisher information（QFI） of the SU（1,1） interferometer with phase shifts in two arms by coherent squeezed vacuum state input, and give the comparison with the result of phase shi...We theoretically study the quantum Fisher information（QFI） of the SU（1,1） interferometer with phase shifts in two arms by coherent squeezed vacuum state input, and give the comparison with the result of phase shift only in one arm.Different from the traditional Mach–Zehnder interferometer, the QFI of single-arm case for an SU（1,1） interferometer can be slightly higher or lower than that of two-arm case, which depends on the intensities of the two arms of the interferometer.For coherent squeezed vacuum state input with a fixed mean photon number, the optimal sensitivity is achieved with a squeezed vacuum input in one mode and the vacuum input in the other.展开更多
Restricted by the development of the transient flow and solute reactive transport models for unsaturated soil, empirical functions have been used previously to calculate the mass of dissolved or precipitated salt when...Restricted by the development of the transient flow and solute reactive transport models for unsaturated soil, empirical functions have been used previously to calculate the mass of dissolved or precipitated salt when they have to be taken into account. Besides, the solute reactive transport process has often been inferred based on measurements that cost lots of time and manpower. HP1 model coupled with PHREEQC provides a suitable tool to improve the estimation of salt distribution during evaporation in saline soil, where the salt dissolution and precipitation cannot be ignored. In this study, we compare the performance of a standard solute transport(SST) model and the HP1 model to examine the improvement of salt distribution estimation. Model results are compared with experimental data sets from four field lysimeters. These columns were exposed to Na Cl solution with different concentrations(3, 30, 100, and 250 g/L) and were undergoing the same strong evaporation boundary condition. The pre-existing Ca SO_(4), Na Cl and Na2SO_(4)loads were 1.15, 0.47 and 0.23 g/(100 g of soil), respectively. Simulation results show that HP1 ameliorates the overestimation of salt content by SST in deeper soil due to the absence of dissolution of pre-existing soluble salts, and prevents the concentration of the solute from exceeding the solubilities which would occur in SST-result. Additionally, HP1-predicted results can help trace the transport process of each solute. Based on the results, we strongly suggest that the management of fields sensitive to salt content should make use of a coupled flow and chemical reaction model.展开更多
The Society of Motion Picture and Television Engineers (SMPTE) Standard 421M, commonly known as VC-1, is a state-of-the-art video compression format that provides highly competitive video quality, from very low throug...The Society of Motion Picture and Television Engineers (SMPTE) Standard 421M, commonly known as VC-1, is a state-of-the-art video compression format that provides highly competitive video quality, from very low through very high bit rates, at a reasonable computational complexity. First, this paper presents fast motion compensation methods. The four motion estimation methods examined are fast, three step search, varying diamond, and 2D logarithmic. These methods use less search points than the full spiral scan used in the VC-1 reference software, which allows for faster motion estimation. Second, this paper presents a residual texture based choice of the block size for the Discrete Cosine Transform (DCT). To determine the block size, data is examined after the residual texture has been calculated. This is in contrast to the VC-1 reference software, which uses calculations at the block level to determine the block size. The residual texture of each block is small and uniform, allowing for simplified block choices.展开更多
With the extensive application of large-scale array antennas,the increasing number of array elements leads to the increasing dimension of received signals,making it difficult to meet the real-time requirement of direc...With the extensive application of large-scale array antennas,the increasing number of array elements leads to the increasing dimension of received signals,making it difficult to meet the real-time requirement of direction of arrival(DOA)estimation due to the computational complexity of algorithms.Traditional subspace algorithms require estimation of the covariance matrix,which has high computational complexity and is prone to producing spurious peaks.In order to reduce the computational complexity of DOA estimation algorithms and improve their estimation accuracy under large array elements,this paper proposes a DOA estimation method based on Krylov subspace and weighted l_(1)-norm.The method uses the multistage Wiener filter(MSWF)iteration to solve the basis of the Krylov subspace as an estimate of the signal subspace,further uses the measurement matrix to reduce the dimensionality of the signal subspace observation,constructs a weighted matrix,and combines the sparse reconstruction to establish a convex optimization function based on the residual sum of squares and weighted l_(1)-norm to solve the target DOA.Simulation results show that the proposed method has high resolution under large array conditions,effectively suppresses spurious peaks,reduces computational complexity,and has good robustness for low signal to noise ratio(SNR)environment.展开更多
In this work,we address the frequency estimation problem of a complex single-tone embedded in the heavy-tailed noise.With the use of the linear prediction(LP)property and l_(1)-norm minimization,a robust frequency est...In this work,we address the frequency estimation problem of a complex single-tone embedded in the heavy-tailed noise.With the use of the linear prediction(LP)property and l_(1)-norm minimization,a robust frequency estimator is developed.Since the proposed method employs the weighted l_(1)-norm on the LP errors,it can be regarded as an extension of the l_(1)-generalized weighted linear predictor.Computer simulations are conducted in the environment of α-stable noise,indicating the superiority of the proposed algorithm,in terms of its robust to outliers and nearly optimal estimation performance.展开更多
基金funded by the Basic scientific research fund projects(Youth Project)of the Educational Department of Liaoning Province in 2023(Grants No.JYTQN2023451)Liaoning Institute of Science and Technology doctoral research initiation fund project in 2023(Grants No.2307B27)+2 种基金Basic Research Project of Higher Education Institutions of Liaoning Provincial Department of Education(Grants No.2024JYTYB-12)the Basic scientific research fund projects(Youth Project)of the Educational Department of Liaoning Province in 2023(Grants No.JYTQN2024-21)Liaoning Institute of Science and Technology doctoral research initiation fund project in 2023(Grants No.2307B26)。
文摘The estimation of glacier flow velocity on a short-term scale is very important for further glacier dynamics research.In this study,10 Sentinel-1 ascending images and 10 Sentinel-1 descending images of Urumqi Glacier No.1 in 2017 were used to calculate the glacier flow velocity in a high coherence period by DIn SAR technology and MAI technology,while the offset tracking technology was used to estimate the glacier flow velocity in a low coherence period.Then,the monthly three-dimensional flow velocity of the glacier was calculated by the Helmert variance component estimation method.Finally,the accuracy of the estimated glacier flow velocity on a monthly scale was evaluated.The results showed that:(1)the monthly scale motion velocity of Urumqi Glacier No.1 in May,June,July,and August 2017 was 0.273 m/month,0.657 m/month,0.582 m/month,and 0.392 m/month,respectively.(2)The accuracy of glacier surface velocity from May 2017 to August 2017 was 0.033 m/month,0.026 m/month,0.034 m/month and 0.037 m/month,respectively.(3)The accuracy of glacier surface flow velocity from May 2017 to August 2017 was 0.018 m/month,0.031 m/month,0.029 m/month and 0.030 m/month,respectively.Therefore,the research methodology based on the Sentinel-1 ascending and descending data and presented in this paper was applicable to the estimation of monthly-scale flow velocity of mountain glaciers.
基金supported in part by the National Natural Science Foundation of China(No.62271248)the Natural Science Foundation of Jiangsu Province(No.BK20230090)the Key Laboratory of Land Satellite Remote Sensing Application through the Ministry of Natural Resources of China(No.KLSMNR-K202303).
文摘In recent years,the development of domestic commercial synthetic aperture radar(SAR)is in full swing,with multiple commercial SAR satellites in orbit,showing great potential in disaster monitoring,natural resource management and deformation observation.Fucheng-1 is the first C-band commercial SAR satellite for interferometric SAR(InSAR)service developed by Spacety China,which marks the gradual maturity of China’s remote sensing data service.Based on the raw data collected by Fucheng-1,this paper firstly introduces the range-Doppler algorithm(RDA),then illustrates the parameter estimation method on the basis of fractional Fourier transform(FrFT)to realize the accurate estimation of azimuth chirp rate,which effectively improves imaging quality.Finally,the L1-norm regularization based sparse imaging method is utilized to reconstruct images from down-sampled data.Experimental results show that the sparse imaging algorithm can accurately reconstruct the down-sampled Fucheng-1 data and suppress sidelobes and clutter.
基金funded by the Macao Foundation,the pre-research project of Civil Aerospace Technologies(Nos.D020308 and D020303)funded by the China National Space Administration,Macao Science and Technology Development Fund(FDCT+1 种基金No.0001/2019/A1)the opening fund of the State Key Laboratory of Lunar and Planetary Sciences(Macao University of Science and Technology,Macao FDCT No.119/2017/A3)。
文摘The Euler angle estimation is a calibration method for vector data measured by the magnetometer on a satellite.It is used to find the relative rotation between the coordinate system of the magnetometer and the satellite(usually determined by Star Imagers).Before launch of the low-orbit,low-inclination Macao Science Satellite-1(known as MSS-1),we simulated the estimation of Euler angles by using the magnetic measurements of the in-orbit Swarm and China Seismo-Electromagnetic Satellite(noted as CSES),with various data combinations.In this study,11 data sets were designed to analyze the estimation results for the MSS-1 orbit by using a joint estimation method of the geomagnetic field model parameters and Euler angles.For the model results,we found that all the spatial power spectral lines showed behavior consistent with that of the CHAOS-7.8 model at low degrees(corresponding to large-scale magnetic signals).The spectra of models without global data coverage deviated much more(by a maximum of~10^(4) nT^(2))from those of the CHAOS-7.8 model at higher degrees.For models with global data coverage and with various data combinations,the spectral lines were distributed similarly.Moreover,the models with accordant power spectral distributions demonstrated different Euler angle estimations.As more vector data at higher latitudes were included,the estimated Euler angles varied monotonically in all three directions.The models with vector data in the same latitude range showed similar Euler angle results,regardless of whether the poleward scalar data were included.The largest value difference was found between the models using vector data within±40°latitudes and those using vector data within±60°latitudes,which reached to~28″.Therefore,we concluded that the inversion of the spherical harmonic Gauss coefficients in our tests was mainly affected by the spatial coverage range of the data,whereas the estimation of Euler angles largely depended on the latitude range where the vector data could be obtained.These results can be used for future in-flight data testing.We expect the estimation of Euler angles to improve as other methods are adopted.
基金the Open Project of Key Laboratory,Xinjiang Uygur Autonomous Region(No.2019D04003)the National Natural Science Foundation of China(NSFC Grant U1703241,41901087)+2 种基金the West Light Foundation of the Chinese Academy of Sciences(No.2018-XBQNZ-B-012)the Key International cooperation project of Chinese Academy of Sciences(No:121311KYSB20160005)the CAS Instrumental development project of Automatic Meteorological Observation System with Multifunctional Modularization(No:Y634241001).
文摘Obtaining the spatial distribution of snow cover in mountainous areas using the optical image of remote sensing technology is difficult because of cloud and fog. In this study, the object-based principle component analysis–support vector machine(PCA–SVM) method is proposed for snow cover mapping through the integration of moderateresolution imaging spectroradiometer(MODIS) snow cover products and the Sentinel-1 synthetic aperture radar(SAR) scattering characteristics. First, derived from the Sentinel-1 A SAR images, the feature parameters, including VV/VH backscatter, scattering entropy, and scattering alpha, were used to describe the variations of snow and non-snow covers. Second, the optimum feature combinations of snow cover were formed from the feature parameters using the principle component analysis(PCA) algorithm. Finally, using the optimum feature combinations, a snow cover map with a 20 m spatial resolution was extracted by means of an object-based SVM classifier. This method was applied in the study area of the Xinyuan County, which is located in the western part of the Tianshan Mountains in Xinjiang, China. The accuracies in this method were analyzed according to the data observed at different experimental sites. Results showed that the snow cover pixels of the extraction were less than those in the actual situation(FB1=93.86, FB2=59.78). The evaluation of the threat score(TS), probability of detection(POD), and false alarm ratio(FAR) for the snow-covered pixels obtained from the two-stage SAR images were different(TS1=86.84, POD1=90.10, FAR1=4.01;TS2=56.40, POD2=57.62, FAR2=3.62). False and misclassifications of the snow cover and non-snow cover pixels were found. Although the classifications were not highly accurate, the approach showed potential for integrating different sources to retrieve the spatial distribution of snow covers during a stable period.
文摘With a low resolution 1-bit ADC on its receiver(RX) side, MIMO with 1-bit ADC took a considerable step in the fulfillment of the hardware complexity constrains of the internet of things(IoT) PHY layer design. However, applying 1-bit ADC at MIMO RX results in severe nonlinear quantization error. By which, almost all received signal amplitude information is completely distorted. Thus, MIMO channel estimation is considered as a major barrier towards practical realization of 1-bit ADC MIMO system. In this paper, two efficient sparsity-based channel estimation techniques are proposed for 1-bit ADC MIMO systems, namely the low complexity sparsity-based channel estimation(LCSCE), and the iterative adaptive sparsity channel estimation(IASCE). In these techniques, the sparsity of the 1-bit ADC MIMO channel is exploited to propose a new adaptive and iterative compressive sensing(CS) recovery algorithm to handle the 1-bit ADC quantization effect. The proposed algorithms are tested with the state-of-the-art 1-bit ADC MIMO constant envelope modulation(MIMO-CEM). The 1-bit ADC MIMO-CEM system is chosen as it fulfills both energy and hardware complexity constraints of the IoT PHY layer. Simulation results reveal the high effectiveness of the proposed algorithms in terms of spectral efficiency(SE) and computational complexity. The proposed LCSCE reduces the computational complexity of the 1-bit ADC MIMO-CEM channel estimation by 86%, while the IASCE reduces it by 96% compared to the recent techniques of MIMO-CEM channel estimation. Moreover, the proposed LCSCE and IASCE improve the spectrum efficiency by 76 % and 73 %, respectively, compared to the recent techniques.
文摘A joint two-dimensional(2D)direction-of-arrival(DOA)and radial Doppler frequency estimation method for the L-shaped array is proposed in this paper based on the compressive sensing(CS)framework.Revised from the conventional CS-based methods where the joint spatial-temporal parameters are characterized in one large scale matrix,three smaller scale matrices with independent azimuth,elevation and Doppler frequency are introduced adopting a separable observation model.Afterwards,the estimation is achieved by L1-norm minimization and the Bayesian CS algorithm.In addition,under the L-shaped array topology,the azimuth and elevation are separated yet coupled to the same radial Doppler frequency.Hence,the pair matching problem is solved with the aid of the radial Doppler frequency.Finally,numerical simulations corroborate the feasibility and validity of the proposed algorithm.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11474095,11654005,and 11234003)the National Key Research and Development Program of China(Grant No.2016YFA0302000)
文摘We theoretically study the quantum Fisher information（QFI） of the SU（1,1） interferometer with phase shifts in two arms by coherent squeezed vacuum state input, and give the comparison with the result of phase shift only in one arm.Different from the traditional Mach–Zehnder interferometer, the QFI of single-arm case for an SU（1,1） interferometer can be slightly higher or lower than that of two-arm case, which depends on the intensities of the two arms of the interferometer.For coherent squeezed vacuum state input with a fixed mean photon number, the optimal sensitivity is achieved with a squeezed vacuum input in one mode and the vacuum input in the other.
基金supported by the National Natural Science Foundation of China (Nos.41572224,U1403282,51709232)the Fundamental Research Funds for the Central Universities,China University of Geosciences (Wuhan) (No.CUG170103)。
文摘Restricted by the development of the transient flow and solute reactive transport models for unsaturated soil, empirical functions have been used previously to calculate the mass of dissolved or precipitated salt when they have to be taken into account. Besides, the solute reactive transport process has often been inferred based on measurements that cost lots of time and manpower. HP1 model coupled with PHREEQC provides a suitable tool to improve the estimation of salt distribution during evaporation in saline soil, where the salt dissolution and precipitation cannot be ignored. In this study, we compare the performance of a standard solute transport(SST) model and the HP1 model to examine the improvement of salt distribution estimation. Model results are compared with experimental data sets from four field lysimeters. These columns were exposed to Na Cl solution with different concentrations(3, 30, 100, and 250 g/L) and were undergoing the same strong evaporation boundary condition. The pre-existing Ca SO_(4), Na Cl and Na2SO_(4)loads were 1.15, 0.47 and 0.23 g/(100 g of soil), respectively. Simulation results show that HP1 ameliorates the overestimation of salt content by SST in deeper soil due to the absence of dissolution of pre-existing soluble salts, and prevents the concentration of the solute from exceeding the solubilities which would occur in SST-result. Additionally, HP1-predicted results can help trace the transport process of each solute. Based on the results, we strongly suggest that the management of fields sensitive to salt content should make use of a coupled flow and chemical reaction model.
文摘The Society of Motion Picture and Television Engineers (SMPTE) Standard 421M, commonly known as VC-1, is a state-of-the-art video compression format that provides highly competitive video quality, from very low through very high bit rates, at a reasonable computational complexity. First, this paper presents fast motion compensation methods. The four motion estimation methods examined are fast, three step search, varying diamond, and 2D logarithmic. These methods use less search points than the full spiral scan used in the VC-1 reference software, which allows for faster motion estimation. Second, this paper presents a residual texture based choice of the block size for the Discrete Cosine Transform (DCT). To determine the block size, data is examined after the residual texture has been calculated. This is in contrast to the VC-1 reference software, which uses calculations at the block level to determine the block size. The residual texture of each block is small and uniform, allowing for simplified block choices.
基金supported by the National Basic Research Program of China。
文摘With the extensive application of large-scale array antennas,the increasing number of array elements leads to the increasing dimension of received signals,making it difficult to meet the real-time requirement of direction of arrival(DOA)estimation due to the computational complexity of algorithms.Traditional subspace algorithms require estimation of the covariance matrix,which has high computational complexity and is prone to producing spurious peaks.In order to reduce the computational complexity of DOA estimation algorithms and improve their estimation accuracy under large array elements,this paper proposes a DOA estimation method based on Krylov subspace and weighted l_(1)-norm.The method uses the multistage Wiener filter(MSWF)iteration to solve the basis of the Krylov subspace as an estimate of the signal subspace,further uses the measurement matrix to reduce the dimensionality of the signal subspace observation,constructs a weighted matrix,and combines the sparse reconstruction to establish a convex optimization function based on the residual sum of squares and weighted l_(1)-norm to solve the target DOA.Simulation results show that the proposed method has high resolution under large array conditions,effectively suppresses spurious peaks,reduces computational complexity,and has good robustness for low signal to noise ratio(SNR)environment.
文摘In this work,we address the frequency estimation problem of a complex single-tone embedded in the heavy-tailed noise.With the use of the linear prediction(LP)property and l_(1)-norm minimization,a robust frequency estimator is developed.Since the proposed method employs the weighted l_(1)-norm on the LP errors,it can be regarded as an extension of the l_(1)-generalized weighted linear predictor.Computer simulations are conducted in the environment of α-stable noise,indicating the superiority of the proposed algorithm,in terms of its robust to outliers and nearly optimal estimation performance.
