[1] Qiu Xiaohui, , Chen Hao, et al. Entropy function optimization for radar imaging [J]. Journal of Southeast University (English Edition), 2009, 25 (4): 427-430. [doi:10.3969/j.issn.1003-7985.2009.04.002]
Copy
Entropy function optimization for radar imaging(
)
基于雷达成像的熵函数优化方法
)Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]
- Volumn:
- 25
- Issue:
- 2009 4
- Page:
- 427-430
- Research Field:
- Electromagnetic Field and Microwave Technology
- Publishing date:
- 2009-12-30
Info
- Title:
- Entropy function optimization for radar imaging
- 基于雷达成像的熵函数优化方法
- Author(s):
- Qiu Xiaohui1; 2; 3; Chen Hao2
-
1College of Communications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
2School of Information and Electrical Engineering, China University of Mining and Technology, Xuzhou 221008, China
3 State Key Laboratory of Millimeter Waves, Southeast University, Nanjing 210096, China
- 邱晓晖1; 2; 3; 陈昊2
- 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
- PACS:
- TN958;TN957.52
- DOI:
- 10.3969/j.issn.1003-7985.2009.04.002
- Abstract:
- 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 multi-dimensional 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.
References:
[1] Berizzi F, Corsini G. Autofocusing of inverse synthetic aperture radar images using contrast optimization [J]. IEEE Transactions on Aerospace and Electronic Systems, 1996, 32(3): 1185-1191.
[2] Berizzi F, Dalle Mese E, Martorella M. Performance analysis of a contrast-based ISAR autofocusing algorithm [C]//Proceedings of the 2002 IEEE Radar Conference. Long Beach, CA, USA, 2002: 200-205.
[3] Martorella M, Berizzi F, Bruscoli S. Use of genetic algorithms for ISAR image autofocusing [C]//Proceedings of the 2004 IEEE Radar Conference. Philadelphia, PA, USA, 2004: 201-206.
[4] Li X, Liu G S, Ni J L. Autofocusing of ISAR imaging based on entropy minimization [J]. IEEE Transactions on Aerospace and Electronic Systems, 1999, 35(4): 1240-1251.
[5] Qiu X H, Zhao Y, Chang A H W, et al. Phase compensation in ISAR imaging: comparison between maximum likelihood-based approach and minimum entropy-based approach [C]//IEEE Antennas and Propagation Society International Symposium. Sendai, Japan, 2004: 2107-2110.
[6] Prickett M J, Chen C C. Principle of inverse synthetic aperture radar imaging [C]//Proceedings of EASCON. Arlington, VA, USA, 1980: 340-345.
[7] Chen C C, Andrews H C. Target-motion-induced radar imaging [J]. IEEE Transactions on Aerospace and Electronic System, 1980, 16(1): 2-14.
[8] Qiu X H, Zhao Y, Heng Wang C A, et al. Consistency study of minimum entropy auto-focusing with phase compensation in ISAR imaging [J]. Journal of Electronics & Information Technology, 2007, 29(8): 1799-1801.(in Chinese)
[9] Zhang K H. COPA—a fast and universal phase adjustment for SAR [J]. Journal of Northwestern Polytechnical University, 2008, 26(4): 481-487.(in Chinese)
[10] Yan G F. Function optimization problem based on genetic algorithm and ant algorithm [J]. Journal of Zhejiang University: Engineering Edition, 2007, 41(3): 427-430.(in Chinese)
[11] Zhu Z D, Qiu X H, She Z S. ISAR motion compensation using modified Doppler centroid tracking algorithm [J]. Transactions of Nanjing University of Aeronautics and Astronautics, 1995, 12(2): 1-8.
Memo
- Memo:
-
Biography: Qiu Xiaohui(1968—), female, doctor, associate professor, qiuxh@njupt.edu.cn.
Foundation items: The Natural Science Foundation of Jiangsu Province(No.BK2008429), Open Research Foundation of State Key Laboratory of Millimeter Waves of Southeast University(No.K200903), China Postdoctoral Science Foundation(No.20080431126), Jiangsu Province Postdoctoral Science Foundation(No.2007337).
Citation: Qiu Xiaohui, Chen Hao. Entropy function optimization for radar imaging[J]. Journal of Southeast University(English Edition), 2009, 25(4): 427-430.