Entropy function optimization for radar imaging  

基于雷达成像的熵函数优化方法(英文)

在线阅读下载全文

作  者:邱晓晖[1,2,3] 陈昊[2] 

机构地区:[1]南京邮电大学通信与信息工程学院,南京210003 [2]中国矿业大学信息与电气工程学院,徐州221008 [3]东南大学毫米波国家重点实验室,南京210096

出  处:《Journal of Southeast University(English Edition)》2009年第4期427-430,共4页东南大学学报(英文版)

基  金:The Natural Science Foundation of Jiangsu Province(NoBK2008429);Open Research Foundation of State Key Laboratory ofMillimeter Waves of Southeast University(NoK200903);China Postdoctoral Science Foundation(No20080431126);Jiangsu Province Postdoctoral Science Foundation(No2007337)

摘  要:The convergence performance of the minimum entropy auto-focusing(MEA) algorithm for inverse synthetic aperture radar(ISAR) imaging is analyzed by simulation. The results show that a local optimal solution problem exists in the MEA algorithm. The cost function of the MEA algorithm is not a downward-convex function of multidimensional phases to be compensated. Only when the initial values of the compensated phases are chosen to be near the global minimal point of the entropy function, the MEA algorithm can converge to a global optimal solution. To study the optimal solution problem of the MEA algorithm, a new scheme of entropy function optimization for radar imaging is presented. First, the initial values of the compensated phases are estimated by using the modified Doppler centroid tracking (DCT)algorithm. Since these values are obtained according to the maximum likelihood (ML) principle, the initial phases can be located near the optimal solution values. Then, a fast MEA algorithm is used for the local searching process and the global optimal solution can be obtained. The simulation results show that this scheme can realize the global optimization of the MEA algorithm and can avoid the selection and adjustment of parameters such as iteration step lengths, threshold values, etc.对ISAR成像的最小熵自聚焦(MEA)算法进行了收敛性分析.仿真结果表明,MEA算法存在局部最优问题,作为其代价函数的ISAR像熵函数并非多维补偿相位的下凸函数.只有当该补偿相位矢量的初值选取合适,使其处于像熵函数的全局最小点附近时,MEA算法才能收敛到全局最优解.针对MEA算法的最优化问题,给出了一种基于雷达成像的熵函数优化方法.该方法首先采用改进的多普勒中心跟踪法估计补偿相位初值.该初值是最大似然准则下的估计结果,可以使初始相位位于最优解附近.然后,利用快速MEA算法进行局部搜索,得到全局最优解.仿真结果表明,该算法不仅实现了MEA算法的全局最优求解,还可避免步长、阈值等参数的选择与调整.

关 键 词:radar signal processing inverse synthetic aperture radar(ISAR) imaging AUTO-FOCUSING 

分 类 号:TN958[电子电信—信号与信息处理] TN957.52[电子电信—信息与通信工程]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象