双基角时变下的空间目标BISAR自聚焦算法

电子与自动控制

本期目录 | 过刊浏览 | 高级检索

前一篇 | 后一篇

双基角时变下的空间目标BISAR自聚焦算法

韩宁^1,3, 王立兵^1,2, 何强¹, 董健¹

1. 军械工程学院雷达工程教研室, 河北石家庄 050003;
2. 中国人民解放军63961部队, 北京 100012;
3. 军械工程学院军械技术研究所, 河北石家庄 050000

收稿日期:2011-10-28 修回日期:2012-01-06 出版日期:2012-10-25 发布日期:2012-10-25
通讯作者: 何强 E-mail:qhe1228@gmail.com
基金资助:
国家"863"计划(2008AA0194)

BISAR Autofocusing Algorithm of Space Targets in Presence of Bistatic Angle Changes

HAN Ning^1,3, WANG Libing^1,2, HE Qiang¹, DONG Jian¹

1. Radar Engineering Faculty, Ordnance Engineering College, Shijiazhuang 050003, China;
2. No.63961 Unit, PLA, Beijing 100012, China;
3. Ordnance Technology Research Institute, Ordnance Engineering College, Shijiazhuang 050000, China

Received:2011-10-28 Revised:2012-01-06 Online:2012-10-25 Published:2012-10-25
Supported by:
National High-tech Research and Development Program of China (2008AA0194)

摘要/Abstract

摘要： 以空间目标为研究对象,针对双基地逆合成孔径雷达(BISAR)成像中双基角变化及同步误差导致的二维ISAR像散焦问题,提出了基于粒子群优化(PSO)的非参数自聚焦算法。算法首先将回波中平动和转动及同步误差等因素导致的相位变化项统一建模,其次将二维图像对比度最大作为优化目标,利用PSO算法对所有高次项相位进行整体优化估计,然后对高阶相位项进行补偿,最后基于补偿后剩余的一阶线性相位项进行方位压缩得到目标的二维ISAR像。算法可解决参数相位误差估计法中因模型误差导致的聚焦精度下降问题,同时也降低了BISAR自聚焦算法的复杂度。通过与参数法自聚焦算法的性能进行对比仿真实验,验证了算法的有效性。

关键词: 空间目标, 双基地逆合成孔径雷达, 自聚焦, 粒子群优化, 对比度最大

Abstract: To absolve the defocusing problem caused by bistatic angle change and synchronization error in bistatic inverse synthetic aperture radar (BISAR) for space targets, a non-parameter autofocusing algorithm based on particle swarm optimization (PSO) is put forward. Phase variation caused by translational motion, rotation and various other factors is modeled as a whole, and based on the optimization aim of maximizing the image contrast, all the second and higher order phase items are estimated using the PSO. Then, image autofocusing is completed using the estimated phase error. Finally, the first order phase item which is left over after phase compensation is used for ISAR imaging. Defocusing caused by model error in the parameter autofocusing algorithm is solved and the complexity of BISAR autofocusing is decreased. The validity of this algorithm is proved by a comparison with the parameter autofocusing algorithm through simulation experiment.

Key words: space target, bistatic inverse synthetic aperture radar, autofocusing, particle swarm optimization, contrast maximization

中图分类号:

韩宁, 王立兵, 何强, 董健. 双基角时变下的空间目标BISAR自聚焦算法[J]. 航空学报, 2012, 33(10): 1864-1871.

HAN Ning, WANG Libing, HE Qiang, DONG Jian. BISAR Autofocusing Algorithm of Space Targets in Presence of Bistatic Angle Changes[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2012, 33(10): 1864-1871.

参考文献

[1] Marco M, James P, Berizzi F, et al. Advances in bistatic inverse synthetic aperture radar. International Radar Conference. Guilin: IET, 2009: 1-6.
[2] Victor C C, Andre D R, Lipps R. Bi-static ISAR range-Doppler imaging and resolution analysis. IEEE Radar Conference. Piscataway: Institute of Electricaland Electronics Engineers Inc, 2009: 1-5.
[3] Zhu R F, Zhang Q, Luo Y, et al. Study on micro-motion feature extraction and imaging of target with rotating parts in bistatic ISAR. Journal of Eletronics & Information Technology, 2010, 32(10): 2359-2364. (in Chinese) 朱仁飞, 张群, 罗迎, 等. 含旋转部件目标双基地ISAR微动特征提取及成像研究. 电子与信息学报, 2010, 32(10): 2359-2364.
[4] Marco M, James P, John H, et al. On bistatic inverse synthetic aperture radar. IEEE Transactions on Aerospace and Electronic Systems, 2007, 43(3): 1125-1134.
[5] James P, John H, Longstaff I D, et al. ISAR imaging using an emulated multistatic radar system. IEEE Transactions on Aerospace and Electronic Systems, 2005, 41(4): 1464-1472.
[6] James P, John H, Mojarrabi B. Improving on the mono-static radar cross section of targets by employing sea clutter to emulate a bistatic radar. IEEE International Geoscience and Remote Sensing Symposium. Toulouse: IEEE, 2003: 324-326.
[7] Gao Z Z. New technologies of high resolution ISAR imaging. Xi’an: National Key Labarotary of Radar Signal Processing, Xidian University, 2009. (in Chinese) 高昭昭. 高分辨ISAR成像新技术研究. 西安:西安电子科技大学雷达信号处理国家重点实验室, 2009.
[8] Zhu X P, Zhang Q, Zhu R F, et al. Study on correction algorithm of migration through resolution cell in bistatic-ISAR. Systems Engineering and Electronics, 2010, 32(9): 1828-1832. (in Chinese) 朱小鹏, 张群, 朱仁飞, 等. 双站ISAR越距离单元徙动分析与校正算法. 系统工程与电子技术, 2010, 32(9): 1828-1832.
[9] Dong J, Shang C X, Gao M G, et al. Research onbistatic ISAR speed compensation of space target. Journal of China Academy of Electronics and Information Technology, 2010, 5(1): 78-85. (in Chinese) 董健, 尚朝轩, 高梅国, 等. 空间目标双基地ISAR成像的速度补偿研究. 中国电子科学研究院学报, 2010, 5(1): 78-85.
[10] Martorella M. Bistatic ISAR image formation in presence of bistatic angle changes and phase synchronisation errors. Proceedings of the EUSAR 2008 Conference. Friedrichshafen: Institution Engineering Technology-Iethertford, 2008: 1-4.
[11] Martorella M, Berizzi F, Bruscoli S. Use of genetic algorithms for ISAR image autofocusing. Proceedings of the IEEE 2004 Radar Conference. Philadelphia, PA: IEEE, 2004: 201-206.
[12] Zhu Y P, Wang H Q, Li X. Autofocus algorithm for ISAR based on total variation norm. Journal of Data Acquisiton & Processing, 2001, 24(S1): 1-7. (in Chinese) 朱玉鹏, 王宏强, 黎湘. 基于最大变差范数准则的ISAR自聚焦方法. 数据采集与处理, 2009, 24(S1): 1-7.
[13] Martorella M, Berizzi F, Haywood B. Contrast maximisation based technique for 2-D ISAR autofocusing. IEE Proceedings on Radar, Sonar and Navigation, 2005, 152(4): 253-262.
[14] Wang J, Liu X, Zhou Z. Minimum-entropy phase adjustment for ISAR. IEE Proceedings on Radar Sonar and Navi-gation, 2004, 151(4): 203-209.
[15] Bernard D S. Microwave imaging of aircraft. Proceedings of IEEE, 1988, 76(12): 1578-1592.
[16] Jiao B, Lian Z G, Gu X S. A dynamic inertia weight particle swarm optimization algorithm. Chaos, Solitons & Fractals, 2008, 37(3): 698-705.

E-mail：hkxb@buaa.edu.cn

关于我们

期刊社服务

专业学科

封面文章

友情链接

主管单位：中国科学技术协会主办单位：中国航空学会北京航空航天大学

双基角时变下的空间目标BISAR自聚焦算法

BISAR Autofocusing Algorithm of Space Targets in Presence of Bistatic Angle Changes

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

[1]	赵柯昕, 甘庆波, 刘静. 天基光学空间目标监测的初轨确定[J]. 航空学报, 2023, 44(1): 326465-326465.
[2]	郭琪磊, 桑为民, 牛俊杰, 袁烨. 复杂气象条件下考虑结冰风险的无人机飞行策略[J]. 航空学报, 2023, 44(1): 627518-627518.
[3]	鲍悦, 陈俊宇, 施天玥, 毛新华. 基于先验误差模型的机载高分宽幅DBF-SAR自聚焦算法[J]. 航空学报, 2021, 42(6): 324502-324502.
[4]	周聪, 闫晓东, 唐硕, 吕石. 大气层内模型预测静态规划拦截中制导[J]. 航空学报, 2021, 42(11): 524912-524912.
[5]	林家泉, 孙凤山, 李亚冲, 庄子波. 基于IPSO-Elman神经网络的飞机客舱能耗预测[J]. 航空学报, 2020, 41(7): 323614-323614.
[6]	阚平, 姜兆亮, 刘玉浩, 王振武. 多植保无人机协同路径规划[J]. 航空学报, 2020, 41(4): 323610-323610.
[7]	刘一鸣, 盛文, 胡冰, 张磊. 相控阵雷达长时跟踪波束调度与波形优化策略[J]. 航空学报, 2020, 41(3): 323519-323519.
[8]	史林, 韩宁, 宋祥君, 王立兵, 崔东辉. 基于虚拟慢时间的双基地ISAR成像算法[J]. 航空学报, 2019, 40(5): 322683-322683.
[9]	郭宝锋, 孙慧贤, 胡文华, 尹文龙, 陈关军. 双基地角时变下的ISAR等效旋转中心估计[J]. 航空学报, 2019, 40(3): 322432-322432.
[10]	周聪, 闫晓东, 唐硕. 圆弧预测变系数显式拦截中制导[J]. 航空学报, 2019, 40(10): 323122-323122.
[11]	韩宁, 李宝晨, 王立兵, 童俊, 郭宝锋. 基于稀疏分解的空间目标双基地ISAR自聚焦算法[J]. 航空学报, 2018, 39(8): 322037-322037.
[12]	朱晓秀, 胡文华, 马俊涛, 郭宝锋, 薛东方. 双基地角时变下的ISAR稀疏孔径自聚焦成像[J]. 航空学报, 2018, 39(8): 322059-322059.
[13]	邵干, 张曙光, 唐鹏. 小型无人机气动参数辨识的新型HGAPSO算法[J]. 航空学报, 2017, 38(4): 120365-120365.
[14]	倪杨, 徐元铭. 金属次加筋结构的单轴压载稳定性优化[J]. 航空学报, 2015, 36(5): 1511-1519.
[15]	韦北余, 朱岱寅, 吴迪. 基于杂波对消-自聚焦的多通道SAR-GMTI[J]. 航空学报, 2015, 36(5): 1585-1595.