A full-polarimetric super-resolution algorithm with spatial smoothing processing is presented for one-dimensional(1-D)radar imaging.The coherence between scattering centers is minimized by using spatial smoothing pr...A full-polarimetric super-resolution algorithm with spatial smoothing processing is presented for one-dimensional(1-D)radar imaging.The coherence between scattering centers is minimized by using spatial smoothing processing(SSP).Then the range and polarimetric scattering matrix of the scattering centers are estimated.The impact of different lengths of the smoothing window on the imaging quality is mainly analyzed with different signal-to-noise ratios(SNR).Simulation and experimental results show that an improved radar super-resolution range profile and more precise estimation can be obtained by adjusting the length of the smoothing window under different SNR conditions.展开更多
Based on Evans’spatial smoothing preprocessing scheme,a new approach calledtwo-direction spatial smoothing preprocessing method is presented.It is proved that the decorre-lation,the effective aperture and the maximum...Based on Evans’spatial smoothing preprocessing scheme,a new approach calledtwo-direction spatial smoothing preprocessing method is presented.It is proved that the decorre-lation,the effective aperture and the maximum number of distinguishable coherent signals(whenarray size is given)of the new method are better than those of the Evans’method.Simulationresults give a comparison between the eigenvector spectrums produced by the two methods.展开更多
The performance the quaternion-Capon( Q-Capon) beamformer degraded when suppressing the interferences that are coherent with the signal of interest( SOI). To tackle the problem,the spatial smoothing technique is a...The performance the quaternion-Capon( Q-Capon) beamformer degraded when suppressing the interferences that are coherent with the signal of interest( SOI). To tackle the problem,the spatial smoothing technique is adopted in quaternion domain to decorrelate the interferences by using linearly and uniformly spaced two-component electromagnetic vector-sensors. By averaging several translational invariant subarray quaternion covariance matrices,the quaternion spatial smoothing is performed to prevent the SOI cancellation phenomena caused by the presence of coherent interferences. It is demonstrated that the quaternion spatial smoothing Q-Capon beamformer can suppress the coherent interferences remarkably while the computational cost is lower than the complex domain long vector spatial smoothing counterpart. Theoretical analyses and simulation results validate the efficacy of the spatially smoothed Q-Capon beamformer in terms of coherent interference suppression capability.展开更多
A brain network consisting of two key parietal nodes, the precuneus and the posterior cingulate cortex, has emerged from recent f MRI studies. Though it is anatomically adjacent to and spatially overlaps with the defa...A brain network consisting of two key parietal nodes, the precuneus and the posterior cingulate cortex, has emerged from recent f MRI studies. Though it is anatomically adjacent to and spatially overlaps with the default mode network(DMN), its function has been associated with memory processing, and it has been referred to as the parietal memory network(PMN). Independent component analysis(ICA) is the most common data-driven method used to extract PMN and DMN simultaneously. However,the effects of data preprocessing and parameter determination in ICA on PMN–DMN segregation are completely unknown. Here, we employ three typical algorithms of group ICA to assess how spatial smoothing and model order influence the degree of PMN–DMN segregation. Our findings indicate that PMN and DMN can only be stably separated using a combination of low-level spatial smoothing and high model order across the three ICA algorithms. We thus argue for more considerations on parametric settings for interpreting DMN data.展开更多
In this study, the North China seismic region was selected as the study area, and evaluation of seismic hazard using the spatial smoothing seismicity model was performed. Firstly, the study area is divided into grids,...In this study, the North China seismic region was selected as the study area, and evaluation of seismic hazard using the spatial smoothing seismicity model was performed. Firstly, the study area is divided into grids, and some parameters (e.g. b-value, M0, Mu, azimuth and M-L relationship) for each seismotectonic model were assigned. Secondly, using elliptical smoothing based on a seismotectonic background model, the statistical earthquake incidence rate in each grid is successively calculated. Lastly, the relevant ground motion attenuation relationship is chosen to assess seismic hazard of general sites. The maps for the distribution of horizontal peak ground acceleration with 10% probability of exceedance in 50 years were obtained by using the seismic hazard analysis method based on grid source. This seismicity model simplifies the methodology of probabilistic seismic hazard analysis, especially appropriate for those places where seismic tectonics is not yet clearly known. This method can provide valuable references for seismic zonation and seismic safety assessment for significant engineering projects.展开更多
为了提高重构相干信号测向算法的估计性能,降低算法运算量,提出了一种基于矩阵重构和酉变换方法的酉矩阵重构算法。该算法首先通过酉变换将阵列接收数据从复值计算转换为实值计算,使计算量大大降低;然后计算阵列协方差矩阵并进行特征值...为了提高重构相干信号测向算法的估计性能,降低算法运算量,提出了一种基于矩阵重构和酉变换方法的酉矩阵重构算法。该算法首先通过酉变换将阵列接收数据从复值计算转换为实值计算,使计算量大大降低;然后计算阵列协方差矩阵并进行特征值分解得到信号子空间,再将信号子空间重构为Toeplitz矩阵实现解相干并再次进行酉变换;最后通过特征值分解得到信号子空间并使用最小二乘法实现波达方向(direction of arrival,DOA)估计。相比于改进的旋转不变性的信号参数(estimation of signal parameters via rotational invariance techniques-like,ESPRIT-Like)算法和空间平滑处理算法,由于消除了噪声影响、构造了Toeplitz矩阵以及充分利用了数据的共轭信息,该算法的估计精度更高、具有更高的运算效率且在ESPRIT-Like算法失效的条件下新算法仍能有效估计DOA。本文算法的运行时间是ESPRIT-Like算法的71.2%,实验结果证明了该方法的有效性和真实性。展开更多
实时定位移动设备在电子对抗系统中至关重要,其性能主要取决于波达角(direction of arrival,DOA)的估计速度。低快拍是快速DOA估计的先决条件。目前基于稀疏重构算法的DOA估计具有适应低快拍的优势,但估计精度受限于初始观测矩阵,且估...实时定位移动设备在电子对抗系统中至关重要,其性能主要取决于波达角(direction of arrival,DOA)的估计速度。低快拍是快速DOA估计的先决条件。目前基于稀疏重构算法的DOA估计具有适应低快拍的优势,但估计精度受限于初始观测矩阵,且估计速度受限于观测矩阵高维度的多次迭代。为此,提出一种空间差分矩阵和稀疏重构耦合的低快拍下高精度快速估计算法。首先利用空间差分矩阵消除非相干信号和噪声对相干信号估计结果的影响,提升初始观测矩阵的准确度;然后对完备字典做前后空间平滑处理,克服高维度信号处理复杂难题,实现快速估计;最后分别估计非相干信号和相干信号。仿真验证结果表明,相比稀疏重构方法,所提方案初值敏感度显著降低,在保障精度相当甚至小幅度提升的前提下,运行时间复杂度降低50%以上。展开更多
A novel method to estimate DOA of coherent signals impinging on a uniform circular array( UCA) is presented in this paper. A virtual uniform linear array (VULA) is first derived by using spatial DFT technique, transfo...A novel method to estimate DOA of coherent signals impinging on a uniform circular array( UCA) is presented in this paper. A virtual uniform linear array (VULA) is first derived by using spatial DFT technique, transforming the UCA from element space to phase mode space to obtain the properties of ordinary ULA, and then the well known spatial smoothing technique is applied to the VULA so that the lost rank of covariance matrix due to signal coherence can be retrieved. This method makes it feasible to use the simple MUSIC algorithm to estimate DOA of coherent signals impinging on a UCA without heavy computation burden. Simulation results strongly verify the effectiveness of the algorithm.展开更多
针对相干信源的波达方向(direction of arrival,DOA)估计问题,传统的空间平滑算法通过减小阵列孔径来解相干,导致估计精度降低。本文以相干分布源为研究对象,首先通过扩展共轭虚拟阵列增大阵列孔径,使用Toeplitz算法进行预估计,根据预...针对相干信源的波达方向(direction of arrival,DOA)估计问题,传统的空间平滑算法通过减小阵列孔径来解相干,导致估计精度降低。本文以相干分布源为研究对象,首先通过扩展共轭虚拟阵列增大阵列孔径,使用Toeplitz算法进行预估计,根据预估计值构建加权矩阵,通过二次加权空间平滑恢复协方差矩阵的秩,消除信号的相干性,结合传播因子算法估计得到目标信源的入射角度。该算法充分利用子阵输出的自相关和互相关信息,改善了阵列孔径带来的精度影响。仿真结果表明,所提算法对相干信源具有良好的分辨能力和估计精度,在低信噪比时鲁棒性较好。展开更多
Spatial modeling has largely been applied in epidemiology and disease modeling. Different methods such as Generalized linear models (GLMs) have been made available to prediction of the claim frequencies. However, due ...Spatial modeling has largely been applied in epidemiology and disease modeling. Different methods such as Generalized linear models (GLMs) have been made available to prediction of the claim frequencies. However, due to heterogeneity nature of policies, the methods do not generate precise and accurate claim frequencies predictions;these parametric statistical methods extensively depend on limiting assumptions (linearity, normality, independence among predictor variables, and a pre-existing functional form relating the criterion variable and predictive variables). This study investigates how to derive a spatial nonparametric model estimator based on smoothing Spline for predicting claim frequencies. The simulation results showed that the proposed estimator is efficient for prediction of claim frequencies than the kernel based counterpart. The estimator derived was applied to a sample of 6500 observations obtained from Cooperative Insurance Company, Kenya for the period of 2018-2020 and the results showed that the proposed method perform<span style="font-family:Verdana;">s</span><span style="font-family:Verdana;"> better than the kernel based counterpart. It is worth noting that inclusion of the spatial effects significantly improves the estimator prediction of claim frequency.</span>展开更多
针对相干信号波达方向(Direction of Arrival,DOA)估计,提出了一种改进的多重信号分类(Multiple Signal Classification,MUSIC)算法。首先,利用信号协方差矩阵的两个最大特征值所对应的特征向量,构造出两个Toeplitz矩阵;然后,利用前后...针对相干信号波达方向(Direction of Arrival,DOA)估计,提出了一种改进的多重信号分类(Multiple Signal Classification,MUSIC)算法。首先,利用信号协方差矩阵的两个最大特征值所对应的特征向量,构造出两个Toeplitz矩阵;然后,利用前后向空间平滑思想得到这两个矩阵的无偏估计并求和;最后,利用MUSIC算法从中估计出相干信号DOA。和已有方法相比,该方法无需损失阵列孔径且具有更优的DOA估计性能。展开更多
由于噪声的存在,现有的相干信号波达方向估计算法在低信噪比、小快拍数和小信号间隔条件下,性能下降严重。针对这一问题,本文提出一种基于总体最小二乘法——旋转不变子空间(Total Least Squares-Estimating Signal Parameter via Rotat...由于噪声的存在,现有的相干信号波达方向估计算法在低信噪比、小快拍数和小信号间隔条件下,性能下降严重。针对这一问题,本文提出一种基于总体最小二乘法——旋转不变子空间(Total Least Squares-Estimating Signal Parameter via Rotational Invariance Techniques,TLS-ESPRIT)算法的改进前后向空间平滑方法,对相干信源波达方向(Direction of Arrival,DOA)进行估计。该方法利用了信号的强相关性和噪声的弱相关性,通过时空相关协方差矩阵重构平滑后的阵列协方差矩阵,并将得到的新协方差矩阵应用于TLS-ESPRIT算法进行DOA估计。通过与其他几种传统的解相干算法建模仿真对比,该算法在相干源之间的DOA距离较近、信噪比(Signal Noise Ratio,SNR)较低和快拍数较小的情况下可以更好地估计波达方向,且具备更高的分辨率和精度。展开更多
基金Supported by the National Naturral Science Foundation of China(61301191)
文摘A full-polarimetric super-resolution algorithm with spatial smoothing processing is presented for one-dimensional(1-D)radar imaging.The coherence between scattering centers is minimized by using spatial smoothing processing(SSP).Then the range and polarimetric scattering matrix of the scattering centers are estimated.The impact of different lengths of the smoothing window on the imaging quality is mainly analyzed with different signal-to-noise ratios(SNR).Simulation and experimental results show that an improved radar super-resolution range profile and more precise estimation can be obtained by adjusting the length of the smoothing window under different SNR conditions.
文摘Based on Evans’spatial smoothing preprocessing scheme,a new approach calledtwo-direction spatial smoothing preprocessing method is presented.It is proved that the decorre-lation,the effective aperture and the maximum number of distinguishable coherent signals(whenarray size is given)of the new method are better than those of the Evans’method.Simulationresults give a comparison between the eigenvector spectrums produced by the two methods.
基金Supported by the National Natural Science Foundation of China(61331019)
文摘The performance the quaternion-Capon( Q-Capon) beamformer degraded when suppressing the interferences that are coherent with the signal of interest( SOI). To tackle the problem,the spatial smoothing technique is adopted in quaternion domain to decorrelate the interferences by using linearly and uniformly spaced two-component electromagnetic vector-sensors. By averaging several translational invariant subarray quaternion covariance matrices,the quaternion spatial smoothing is performed to prevent the SOI cancellation phenomena caused by the presence of coherent interferences. It is demonstrated that the quaternion spatial smoothing Q-Capon beamformer can suppress the coherent interferences remarkably while the computational cost is lower than the complex domain long vector spatial smoothing counterpart. Theoretical analyses and simulation results validate the efficacy of the spatially smoothed Q-Capon beamformer in terms of coherent interference suppression capability.
基金supported by the National Basic Research(973)Program(2015CB351702)the National Natural Science Foundation of China(81571756,81270023,81278412,81171409,81000583,81471740,81220108014)+2 种基金Beijing Nova Program(XXJH2015B079 to Z.Y.)the Outstanding Young Investigator Award of Institute of Psychology,Chinese Academy of Sciences(to Z.Y.)the Key Research Program and the Hundred Talents Program of the Chinese Academy of Sciences(KSZD-EW-TZ-002 to X.N.Z)
文摘A brain network consisting of two key parietal nodes, the precuneus and the posterior cingulate cortex, has emerged from recent f MRI studies. Though it is anatomically adjacent to and spatially overlaps with the default mode network(DMN), its function has been associated with memory processing, and it has been referred to as the parietal memory network(PMN). Independent component analysis(ICA) is the most common data-driven method used to extract PMN and DMN simultaneously. However,the effects of data preprocessing and parameter determination in ICA on PMN–DMN segregation are completely unknown. Here, we employ three typical algorithms of group ICA to assess how spatial smoothing and model order influence the degree of PMN–DMN segregation. Our findings indicate that PMN and DMN can only be stably separated using a combination of low-level spatial smoothing and high model order across the three ICA algorithms. We thus argue for more considerations on parametric settings for interpreting DMN data.
基金funded by the Special Fund for Fundamental Research of Central-level Public Interest Institutions,China(ZDJ2011-13)
文摘In this study, the North China seismic region was selected as the study area, and evaluation of seismic hazard using the spatial smoothing seismicity model was performed. Firstly, the study area is divided into grids, and some parameters (e.g. b-value, M0, Mu, azimuth and M-L relationship) for each seismotectonic model were assigned. Secondly, using elliptical smoothing based on a seismotectonic background model, the statistical earthquake incidence rate in each grid is successively calculated. Lastly, the relevant ground motion attenuation relationship is chosen to assess seismic hazard of general sites. The maps for the distribution of horizontal peak ground acceleration with 10% probability of exceedance in 50 years were obtained by using the seismic hazard analysis method based on grid source. This seismicity model simplifies the methodology of probabilistic seismic hazard analysis, especially appropriate for those places where seismic tectonics is not yet clearly known. This method can provide valuable references for seismic zonation and seismic safety assessment for significant engineering projects.
文摘为了提高重构相干信号测向算法的估计性能,降低算法运算量,提出了一种基于矩阵重构和酉变换方法的酉矩阵重构算法。该算法首先通过酉变换将阵列接收数据从复值计算转换为实值计算,使计算量大大降低;然后计算阵列协方差矩阵并进行特征值分解得到信号子空间,再将信号子空间重构为Toeplitz矩阵实现解相干并再次进行酉变换;最后通过特征值分解得到信号子空间并使用最小二乘法实现波达方向(direction of arrival,DOA)估计。相比于改进的旋转不变性的信号参数(estimation of signal parameters via rotational invariance techniques-like,ESPRIT-Like)算法和空间平滑处理算法,由于消除了噪声影响、构造了Toeplitz矩阵以及充分利用了数据的共轭信息,该算法的估计精度更高、具有更高的运算效率且在ESPRIT-Like算法失效的条件下新算法仍能有效估计DOA。本文算法的运行时间是ESPRIT-Like算法的71.2%,实验结果证明了该方法的有效性和真实性。
文摘实时定位移动设备在电子对抗系统中至关重要,其性能主要取决于波达角(direction of arrival,DOA)的估计速度。低快拍是快速DOA估计的先决条件。目前基于稀疏重构算法的DOA估计具有适应低快拍的优势,但估计精度受限于初始观测矩阵,且估计速度受限于观测矩阵高维度的多次迭代。为此,提出一种空间差分矩阵和稀疏重构耦合的低快拍下高精度快速估计算法。首先利用空间差分矩阵消除非相干信号和噪声对相干信号估计结果的影响,提升初始观测矩阵的准确度;然后对完备字典做前后空间平滑处理,克服高维度信号处理复杂难题,实现快速估计;最后分别估计非相干信号和相干信号。仿真验证结果表明,相比稀疏重构方法,所提方案初值敏感度显著降低,在保障精度相当甚至小幅度提升的前提下,运行时间复杂度降低50%以上。
文摘A novel method to estimate DOA of coherent signals impinging on a uniform circular array( UCA) is presented in this paper. A virtual uniform linear array (VULA) is first derived by using spatial DFT technique, transforming the UCA from element space to phase mode space to obtain the properties of ordinary ULA, and then the well known spatial smoothing technique is applied to the VULA so that the lost rank of covariance matrix due to signal coherence can be retrieved. This method makes it feasible to use the simple MUSIC algorithm to estimate DOA of coherent signals impinging on a UCA without heavy computation burden. Simulation results strongly verify the effectiveness of the algorithm.
文摘针对相干信源的波达方向(direction of arrival,DOA)估计问题,传统的空间平滑算法通过减小阵列孔径来解相干,导致估计精度降低。本文以相干分布源为研究对象,首先通过扩展共轭虚拟阵列增大阵列孔径,使用Toeplitz算法进行预估计,根据预估计值构建加权矩阵,通过二次加权空间平滑恢复协方差矩阵的秩,消除信号的相干性,结合传播因子算法估计得到目标信源的入射角度。该算法充分利用子阵输出的自相关和互相关信息,改善了阵列孔径带来的精度影响。仿真结果表明,所提算法对相干信源具有良好的分辨能力和估计精度,在低信噪比时鲁棒性较好。
文摘Spatial modeling has largely been applied in epidemiology and disease modeling. Different methods such as Generalized linear models (GLMs) have been made available to prediction of the claim frequencies. However, due to heterogeneity nature of policies, the methods do not generate precise and accurate claim frequencies predictions;these parametric statistical methods extensively depend on limiting assumptions (linearity, normality, independence among predictor variables, and a pre-existing functional form relating the criterion variable and predictive variables). This study investigates how to derive a spatial nonparametric model estimator based on smoothing Spline for predicting claim frequencies. The simulation results showed that the proposed estimator is efficient for prediction of claim frequencies than the kernel based counterpart. The estimator derived was applied to a sample of 6500 observations obtained from Cooperative Insurance Company, Kenya for the period of 2018-2020 and the results showed that the proposed method perform<span style="font-family:Verdana;">s</span><span style="font-family:Verdana;"> better than the kernel based counterpart. It is worth noting that inclusion of the spatial effects significantly improves the estimator prediction of claim frequency.</span>
文摘针对相干信号波达方向(Direction of Arrival,DOA)估计,提出了一种改进的多重信号分类(Multiple Signal Classification,MUSIC)算法。首先,利用信号协方差矩阵的两个最大特征值所对应的特征向量,构造出两个Toeplitz矩阵;然后,利用前后向空间平滑思想得到这两个矩阵的无偏估计并求和;最后,利用MUSIC算法从中估计出相干信号DOA。和已有方法相比,该方法无需损失阵列孔径且具有更优的DOA估计性能。
文摘由于噪声的存在,现有的相干信号波达方向估计算法在低信噪比、小快拍数和小信号间隔条件下,性能下降严重。针对这一问题,本文提出一种基于总体最小二乘法——旋转不变子空间(Total Least Squares-Estimating Signal Parameter via Rotational Invariance Techniques,TLS-ESPRIT)算法的改进前后向空间平滑方法,对相干信源波达方向(Direction of Arrival,DOA)进行估计。该方法利用了信号的强相关性和噪声的弱相关性,通过时空相关协方差矩阵重构平滑后的阵列协方差矩阵,并将得到的新协方差矩阵应用于TLS-ESPRIT算法进行DOA估计。通过与其他几种传统的解相干算法建模仿真对比,该算法在相干源之间的DOA距离较近、信噪比(Signal Noise Ratio,SNR)较低和快拍数较小的情况下可以更好地估计波达方向,且具备更高的分辨率和精度。