基于三迭代与二阶锥规划的机载MIMO雷达稳健降维STAP方法

doi:10.7527/S1000-6893.2015.0070

电子与控制

本期目录 | 过刊浏览 | 高级检索

前一篇 | 后一篇

基于三迭代与二阶锥规划的机载MIMO雷达稳健降维STAP方法

王珽, 赵拥军

信息工程大学导航与空天目标工程学院, 郑州 450001

收稿日期:2014-12-10 修回日期:2015-03-10 出版日期:2015-11-15 发布日期:2015-03-26
通讯作者: 王珽,Tel.:0371-81622588,E-mail:wangtingsp@163.com E-mail:wangtingsp@163.com
作者简介:王珽,男,博士研究生。主要研究方向:机载MIMO雷达空时自适应处理技术。Tel:0371-81622588,E-mail:wangtingsp@163.com;赵拥军,男,教授,博士生导师。主要研究方向:雷达信号处理、阵列信号处理。Tel:0371-81622581,E-mail:zhaoyjzz@163.com
基金资助:
国家自然科学基金(41301481)

Robust reduced-dimension STAP method for airborne MIMO radar based on TRIA and SOCP

WANG Ting, ZHAO Yongjun

School of Navigation and Aerospace Target Engineering, Information Engineering University, Zhengzhou 450001, China

Received:2014-12-10 Revised:2015-03-10 Online:2015-11-15 Published:2015-03-26
Supported by:
National Natural Science Foundation of China (41301481)

摘要/Abstract

摘要：

针对机载多输入多输出(MIMO)雷达空时自适应处理(STAP)中期望目标导向矢量的失配问题,提出一种基于三迭代(TRIA)与二阶锥规划(SOCP)的稳健降维MIMO-STAP方法。首先将MIMO-STAP权矢量分解为发射、接收、多普勒3个低维权矢量的Kronecker积,然后分别限定实际发射、接收、多普勒导向矢量与假定导向矢量之间的误差范数边界,通过优化最差性能,利用SOCP对各个低维权矢量进行三迭代求解,最后进行权矢量合成。该方法在保证机载MIMO雷达获取稳健STAP性能的同时,通过三迭代降维处理,能够有效降低训练样本数需求与运算复杂度,因此更具有实际应用价值。仿真结果验证了算法的有效性。

关键词: 机载MIMO雷达, 空时自适应处理, 稳健, 降维, 三迭代, 二阶锥规划

Abstract:

To solve the problem of the mismatch errors between the actual and presumed signal steering vectors in airborne multiple-input multiple-output (MIMO) radar space-time adaptive processing (STAP), a robust reduced-dimension MIMO-STAP method based on tri-iterative algorithm (TRIA) and second-order cone programming (SOCP) is proposed. Firstly the MIMO-STAP weight vector is decomposed into the Kronecker product of the transmitting, the receiving and the Doppler weight vectors. Then by imposing a bound on the errors between the actual transmitting, receiving and Doppler steering vectors and the presumed steering vectors, SOCP is used to optimize the worst case performance. The three low-dimension weight vectors are resolved based on the TRIA to synthesize the final weight vector. The proposed method can significantly decrease the training sample requirement and the computational complexity while maintaining the robust STAP performance of airborne MIMO radar, which is more valuable for practical engineering application. Simulation results verify the effectiveness of the proposed method.

Key words: airborne multiple-input multiple-output (MIMO) radar, space-time adaptive processing, robustness, dimension reduction, tri-iterative algorithm, second-order cone programming

中图分类号:

V243.2
TN957

王珽, 赵拥军. 基于三迭代与二阶锥规划的机载MIMO雷达稳健降维STAP方法[J]. 航空学报, 2015, 36(11): 3706-3714.

WANG Ting, ZHAO Yongjun. Robust reduced-dimension STAP method for airborne MIMO radar based on TRIA and SOCP[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2015, 36(11): 3706-3714.

参考文献

[1] Fisher E, Haimovich A M, Blum R S. Spatial diversity in radar-models and detection performance[J]. IEEE Transactions on Signal Processing, 2006, 54(3):823-838.
[2] Haimovich A M, Blum R S, Lenard J, et al. MIMO radar with widely separated antennas[J]. IEEE Signal Processing Magazine, 2008, 25(1):116-129.
[3] Li J, Stoica P. MIMO radar with collocated antennas[J]. IEEE Signal Processing Magazine, 2007, 24(5):106-114.
[4] Bliss D W, Forsythe K W. Multiple-input multiple-output (MIMO) radar and imaging:Degrees of freedom and resolution[C]//Proceedings of the 37th Asilomar Conference on Signals, Systems and Computers, 2003:54-59.
[5] Guerci J R. Space time adaptive processing for radar[M]. Boston:Artech House, 2003:3-55.
[6] Klemm R. Principles of space-time adaptive processing[M]. London:The Institution of Electrical Engineers, 2002:5-45.
[7] Reed I S, Mallett J D, Brennan L E. Rapid convergence rate in adaptive arrays[J]. IEEE Transactions on Aerospace and Electronic Systems, 1974, 10(6):853-863.
[8] Chen C Y, Vaidyanathan P P. MIMO radar space-time adaptive processing using prolate spheroidal wave functions[J]. IEEE Transactions on Signal Processing, 2008, 56(2):623-634.
[9] Lyu H, Feng D Z, He J, et al. A simplified eigencanceler for airborne MIMO radar clutter suppression[J]. Acta Aeronautica et Astronautica Sinica, 2011, 32(5):866-870(in Chinese).吕晖,冯大政,和洁,等.一种简化的机载MIMO雷达杂波特征相消器[J].航空学报, 2011, 32(5):866-870.
[10] Zhai W W, Zhang G, Liu W B. Study of reduced-rank STAP based on estimation of clutter subspace for MIMO radar[J]. Acta Aeronautica et Astronautica Sinica, 2010, 31(9):1824-1831(in Chinese).翟伟伟,张弓,刘文波.基于杂波子空间估计的MIMO雷达降维STAP研究[J].航空学报, 2010, 31(9):1824-1831.
[11] Xiang C, Feng D Z, Lyu H. Three-dimensional reduced-dimension transformation for MIMO radar space-time adaptive processing[J]. Signal Processing, 2011, 91(8):2121-2126.
[12] Ahmadi M, Mohamed-pour K. Robust space-time adaptive processing against Doppler and direction-of-arrival mismatches[C]//Proceedings of Microwaves, Radar and Remote Sensing Symposium. Piscataway, NJ:IEEE Press,2011:305-308.
[13] Liu C F. Research on robust adaptive beamforming and space-time adaptive preprocessing algorithms[D]. Xi'an:Xidian University, 2008(in Chinese).刘聪锋.稳健的自适应波束形成与空时自适应处理算法研究[D].西安:西安电子科技大学, 2008.
[14] Wang H Y, Liao G S, Li J, et al. Robust waveform design for MIMO-STAP to improve the worst-case detection performance[J]. EURASIP Journal on Advances in Signal Processing, 2013, 52:1-8.
[15] Sturm J F. Using SeDuMi 1.02, a MATLAB toolbox for optimization over symmetric cones[J]. Optimization Methods and Software, 1999, 11(1-4):625-653.
[16] Vorobyov S A, Gershman A B, Luo Z Q. Robust adaptive beamforming using worst-case performance optimization:A solution to the signal mismatch problem[J]. IEEE Transactions on Signal Processing, 2003, 51(2):313-324.

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

基于三迭代与二阶锥规划的机载MIMO雷达稳健降维STAP方法

Robust reduced-dimension STAP method for airborne MIMO radar based on TRIA and SOCP

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]	赵欢, 高正红, 夏露. 基于新型多可信度代理模型的多目标优化方法[J]. 航空学报, 2023, 44(6): 126962-126962.
[2]	赵欢, 高正红, 夏露. 基于新型高维代理模型的气动外形设计方法[J]. 航空学报, 2023, 44(5): 126924-126924.
[3]	李航行, 胡迪科, 吴邵庆. 复合材料整流罩减振降噪的动力吸振器设计[J]. 航空学报, 2022, 43(5): 225249-225249.
[4]	赵欢, 高正红, 夏露. 高速自然层流翼型高效气动稳健优化设计方法[J]. 航空学报, 2022, 43(1): 124894-124894.
[5]	胡政文, 张保强, 邓振鸿. 概率盒全局灵敏度和活跃子空间跨层降维[J]. 航空学报, 2021, 42(9): 224582-224582.
[6]	章涛, 钟伦珑, 来燃, 郭骏骋. 基于稀疏贝叶斯学习的字典失配杂波空时谱估计方法[J]. 航空学报, 2021, 42(6): 324592-324592.
[7]	马宗占, 许志, 唐硕, 张迁. 一种改进的运载火箭迭代制导方法[J]. 航空学报, 2021, 42(2): 324218-324218.
[8]	王娜娜, 解青, 苏星宇, 任祝寅. 湍流燃烧机理和调控的活性子空间分析方法[J]. 航空学报, 2021, 42(12): 625228-625228.
[9]	王辰, 左彦飞, 江志农, 胡明辉, 冯坤. 全转速系数矩阵降维重构的燃机不平衡量逆推方法[J]. 航空学报, 2020, 41(11): 223670-223670.
[10]	罗佳奇, 陈泽帅, 曾先. 考虑几何设计参数不确定性影响的涡轮叶栅稳健性气动设计优化[J]. 航空学报, 2020, 41(10): 123826-123826.
[11]	张瞩熹, 朱熙, 朱少川, 张明远, 杜文博. 基于核主成分分析的空域复杂度无监督评估[J]. 航空学报, 2019, 40(8): 322969-322969.
[12]	蒋献, 王言, 孟敏. 失效概率矩独立全局灵敏度分析的高效算法[J]. 航空学报, 2019, 40(3): 222414-222414.
[13]	毕权杨, 李旦, 张建秋. 空时自适应处理张量波束成形器的外积合成法[J]. 航空学报, 2019, 40(10): 322939-322939.
[14]	张政, 周长聪, 戴志豪, 任哲先, 岳珠峰. 基于重要性测度降维的液压管路稳健优化设计[J]. 航空学报, 2018, 39(8): 421902-421902.
[15]	冯凯旋, 吕震宙, 蒋献. 基于偏导数的全局灵敏度指标的高效求解方法[J]. 航空学报, 2018, 39(3): 221699-221699.