现有的波达方向(Direction of Arrival,DOA)估计方法大多依赖于阵列导向矩阵的精确无偏条件,而实际工程中由于时钟偏移、阵元位置偏差的存在导致该条件往往难以满足.为匹配阵列实际接收条件,本文基于部分校准嵌套阵列,提出了一种增益相...现有的波达方向(Direction of Arrival,DOA)估计方法大多依赖于阵列导向矩阵的精确无偏条件,而实际工程中由于时钟偏移、阵元位置偏差的存在导致该条件往往难以满足.为匹配阵列实际接收条件,本文基于部分校准嵌套阵列,提出了一种增益相位误差下的DOA估计新方法.该方法首先利用连乘子函数和简单的代数运算完成初始增益相位误差估计,然后通过协方差矩阵向量化和稀疏表示理论构建具有连续自由度的稀疏表示向量模型,最后考虑有效样本的影响,在初始增益相位误差估计的基础上应用稀疏总体最小均方(Sparse total least squares,STLS)算法完成波达方向估计.本文所提方法不仅对阵列增益相位误差不敏感,而且可依靠嵌套阵列高自由度特性和STLS算法的抗扰动特性获得改进的分辨率和估计精度,计算机仿真结果验证了所提算法的有效性.展开更多
A recently released XMM-Newton note revealed a significant calibration issue between nuclear spectroscopic telescope array(NuSTAR)and XMM-Newton European Photon Imaging Camera(EPIC)and provided an empirical correction...A recently released XMM-Newton note revealed a significant calibration issue between nuclear spectroscopic telescope array(NuSTAR)and XMM-Newton European Photon Imaging Camera(EPIC)and provided an empirical correction to the EPIC effective area.To quantify the bias caused by the calibration issue in the joint analysis of XMM-NuSTAR spectra and verify the effectiveness of the correction,in this work,we perform joint-fitting of the NuSTAR and EPIC-pn spectra for a large sample of 104 observation pairs of 44 X-ray bright active galactic nuclei(AGN).The spectra were extracted after requiring perfect simultaneity between the XMM-Newton and NuSTAR exposures(merging good time intervals(GTIs)from two missions)to avoid bias due to the rapid spectral variability of the AGN.Before the correction,the EPIC-pn spectra are systematically harder than the corresponding NuSTAR spectra by■subsequently yielding significantly underestimated cutoff energy E_(cut)and the strength of reflection component R when performing joint-fitting.We confirm that the correction is highly effective and can commendably erase the discrepancy in best-fitΓ,E_(cut),and R.We thus urge the community to apply the correction when joint-fitting XMM-NuSTAR spectra,but note that the correction is limited to 3–12 keV and therefore not applicable when the soft X-ray band data are included.Besides,we show that as merging GTIs from two missions would cause severe loss of NuSTAR net exposure time,in many cases,joint-fitting yields no advantage compared with utilizing NuSTAR data alone.Finally,We present a technical note on filtering periods of high background flares for XMM-Newton EPIC-pn exposures in the small window(SW)mode.展开更多
The sensor array calibration methods tailored to uniform rectangular array(URA)in the presence of mutual coupling and sensor gain-and-phase errors were addressed.First,the mutual coupling model of the URA was studied,...The sensor array calibration methods tailored to uniform rectangular array(URA)in the presence of mutual coupling and sensor gain-and-phase errors were addressed.First,the mutual coupling model of the URA was studied,and then a set of steering vectors corresponding to distinct locations were numerically computed with the help of several time-disjoint auxiliary sources with known directions.Then,the optimization modeling with respect to the array error matrix(defined by the product of mutual coupling matrix and sensor gain-and-phase errors matrix)was constructed.Two preferable algorithms(called algorithm I and algorithm II)were developed to minimize the cost function.In algorithm I,the array error matrix was regarded as a whole parameter to be estimated,and the exact solution was available.Compared to some existing algorithms with the similar computation framework,algorithm I can make full use of the potentially linear characteristics of URA's error matrix,thus,the calibration precision was obviously enhanced.In algorithm II,the array error matrix was decomposed into two matrix parameters to be optimized.Compared to algorithm I,it can further decrease the number of unknowns and,thereby,yield better estimation accuracy.However,algorithm II was incapable of producing the closed-form solution and the iteration operation was unavoidable.Simulation results validate the excellent performances of the two novel algorithms compared to some existing calibration algorithms.展开更多
文摘针对高频地波雷达系统的工程应用,提出一种基于自动识别系统(automatic identification system,AIS)信息相关系数法进行阵列幅相误差校准的方法。该方法利用低信噪比的舰船回波信号,可以实现同步校正,不需要专门部署应答器,且成本低,对于不能借助直达波校准的单基地高频地波雷达系统同样适用。分析现场的实测数据结果表明,通过该方法对阵列幅相误差进行校准可以获得稳定的幅度、相位校准值,校准后多信号分类(multiple signal classification,MUSIC)空间谱估计方位角的准确性和分辨率得到大幅度提高,进而显著改善利用MUSIC算法估计海流方位角的高频地波雷达系统海流探测性能。
文摘现有的波达方向(Direction of Arrival,DOA)估计方法大多依赖于阵列导向矩阵的精确无偏条件,而实际工程中由于时钟偏移、阵元位置偏差的存在导致该条件往往难以满足.为匹配阵列实际接收条件,本文基于部分校准嵌套阵列,提出了一种增益相位误差下的DOA估计新方法.该方法首先利用连乘子函数和简单的代数运算完成初始增益相位误差估计,然后通过协方差矩阵向量化和稀疏表示理论构建具有连续自由度的稀疏表示向量模型,最后考虑有效样本的影响,在初始增益相位误差估计的基础上应用稀疏总体最小均方(Sparse total least squares,STLS)算法完成波达方向估计.本文所提方法不仅对阵列增益相位误差不敏感,而且可依靠嵌套阵列高自由度特性和STLS算法的抗扰动特性获得改进的分辨率和估计精度,计算机仿真结果验证了所提算法的有效性.
基金supported by the National Natural Science Foundation of China(12033006,12192221,123B2042).
文摘A recently released XMM-Newton note revealed a significant calibration issue between nuclear spectroscopic telescope array(NuSTAR)and XMM-Newton European Photon Imaging Camera(EPIC)and provided an empirical correction to the EPIC effective area.To quantify the bias caused by the calibration issue in the joint analysis of XMM-NuSTAR spectra and verify the effectiveness of the correction,in this work,we perform joint-fitting of the NuSTAR and EPIC-pn spectra for a large sample of 104 observation pairs of 44 X-ray bright active galactic nuclei(AGN).The spectra were extracted after requiring perfect simultaneity between the XMM-Newton and NuSTAR exposures(merging good time intervals(GTIs)from two missions)to avoid bias due to the rapid spectral variability of the AGN.Before the correction,the EPIC-pn spectra are systematically harder than the corresponding NuSTAR spectra by■subsequently yielding significantly underestimated cutoff energy E_(cut)and the strength of reflection component R when performing joint-fitting.We confirm that the correction is highly effective and can commendably erase the discrepancy in best-fitΓ,E_(cut),and R.We thus urge the community to apply the correction when joint-fitting XMM-NuSTAR spectra,but note that the correction is limited to 3–12 keV and therefore not applicable when the soft X-ray band data are included.Besides,we show that as merging GTIs from two missions would cause severe loss of NuSTAR net exposure time,in many cases,joint-fitting yields no advantage compared with utilizing NuSTAR data alone.Finally,We present a technical note on filtering periods of high background flares for XMM-Newton EPIC-pn exposures in the small window(SW)mode.
基金Project(61201381)supported by the National Natural Science Foundation of ChinaProject(YP12JJ202057)supported by the Future Development Foundation of Zhengzhou Information Science and Technology College,China
文摘The sensor array calibration methods tailored to uniform rectangular array(URA)in the presence of mutual coupling and sensor gain-and-phase errors were addressed.First,the mutual coupling model of the URA was studied,and then a set of steering vectors corresponding to distinct locations were numerically computed with the help of several time-disjoint auxiliary sources with known directions.Then,the optimization modeling with respect to the array error matrix(defined by the product of mutual coupling matrix and sensor gain-and-phase errors matrix)was constructed.Two preferable algorithms(called algorithm I and algorithm II)were developed to minimize the cost function.In algorithm I,the array error matrix was regarded as a whole parameter to be estimated,and the exact solution was available.Compared to some existing algorithms with the similar computation framework,algorithm I can make full use of the potentially linear characteristics of URA's error matrix,thus,the calibration precision was obviously enhanced.In algorithm II,the array error matrix was decomposed into two matrix parameters to be optimized.Compared to algorithm I,it can further decrease the number of unknowns and,thereby,yield better estimation accuracy.However,algorithm II was incapable of producing the closed-form solution and the iteration operation was unavoidable.Simulation results validate the excellent performances of the two novel algorithms compared to some existing calibration algorithms.
