天线增益校准是射电天文观测数据处理过程中的一个关键步骤。分析了经典的天线增益校准算法Antsol的基本原理,并基于Python对Antsol算法进行了高性能实现,所完成的程序代码已经集成到平方公里阵列(Square Kilometre Array,SKA)的射电天...天线增益校准是射电天文观测数据处理过程中的一个关键步骤。分析了经典的天线增益校准算法Antsol的基本原理,并基于Python对Antsol算法进行了高性能实现,所完成的程序代码已经集成到平方公里阵列(Square Kilometre Array,SKA)的射电天文模拟校准成像软件(Radio Astronomy Simulation,Calibration and Imaging Library,RASCIL)中,不仅为当前平方公里阵列数据处理提供了支撑,也为未来数据处理的性能优化提供算法参考。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
文摘天线增益校准是射电天文观测数据处理过程中的一个关键步骤。分析了经典的天线增益校准算法Antsol的基本原理,并基于Python对Antsol算法进行了高性能实现,所完成的程序代码已经集成到平方公里阵列(Square Kilometre Array,SKA)的射电天文模拟校准成像软件(Radio Astronomy Simulation,Calibration and Imaging Library,RASCIL)中,不仅为当前平方公里阵列数据处理提供了支撑,也为未来数据处理的性能优化提供算法参考。
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.
