空域数据重排的后多普勒自适应处理方法

doi:10.7527/S1000-6893.2015.0002

电子与控制

本期目录 | 过刊浏览 | 高级检索

前一篇 | 后一篇

空域数据重排的后多普勒自适应处理方法

周延, 冯大政, 朱国辉

西安电子科技大学雷达信号处理国家重点实验室, 西安 710071

收稿日期:2014-07-10 修回日期:2015-01-03 出版日期:2015-09-15 发布日期:2015-01-15
通讯作者: 周延男, 博士研究生。主要研究方向: 空时自适应信号处理, 阵列信号处理。Tel:. 029-88201693 E-mail: yanzhou@stu.xidian.edu.cn E-mail:yanzhou@stu.xidian.edu.cn
作者简介:冯大政男, 教授, 博士生导师。主要研究方向: 雷达成像, 阵列信号处理, 盲信号处理, 神经网络。 E-mail: dzfeng@xidian.edu.cn;朱国辉男, 博士研究生。主要研究方向: 无源定位技术。 E-mail: zhugh@stu.xidian.edu.cn
基金资助:
国家自然科学基金 (61271293)

Post-Doppler adaptive processing method based on spatial data rearrangement

ZHOU Yan, FENG Dazheng, ZHU Guohui

National Laboratory of Radar Signal Processing, Xidian University, Xi'an 710071, China

Received:2014-07-10 Revised:2015-01-03 Online:2015-09-15 Published:2015-01-15
Supported by:
National Natural Science Foundation of China (61271293)

摘要/Abstract

摘要：

传统的后多普勒自适应处理方法,如因子法(FA)和扩展因子法(EFA)虽然能大大降低自适应处理时的运算量和独立同分布样本的需求量,但由于实际中均匀训练样本数目的限制,当天线阵元数进一步增大时,FA和EFA抑制杂波和检测动目标的能力会显著恶化。针对这一问题,提出了一种空域数据重排的后多普勒自适应处理方法。该方法将多普勒滤波后的空域数据重排为一行列数相近的矩阵,空域滤波器权系数也表示成可分离的形式,从而得到一双二次代价函数,利用循环迭代的思想求解权系数。实验表明该方法具有快速收敛,所需训练样本少的优点,尤其在大阵列、小样本条件下该方法抑制杂波的性能明显优于FA和EFA。

关键词: 空时自适应处理, 杂波抑制, 收敛性, 降维, 循环迭代

Abstract:

The traditional post-Doppler adaptive beam-forming approaches such as factored approach (FA) and extended factored approach (EFA) can significantly reduce the computation-complexity and training sample requirement in adaptive processing. However, their clutter suppression and moving target detection ability can be notably degraded with the increasing number of antenna elements since the homogeneous training samples in real clutter environment are always limited. Aimed at this problem, the post-Doppler adaptive processing method based on the spatial data rearrangement is proposed. This method rearranges the spatial data vector, after being filtered by Doppler, into a matrix that has close columns and rows. The spatial weights are also re-expressed as a separation form. Then a bi-quadratic cost function is obtained. The cyclic iteration is applied to solving the desired weight vector. Experimental results show that the proposed method has the advantages of fast convergence and small training sample requirement. It also has greater clutter suppression ability especially in large antenna array elements compared to FA and EFA.

Key words: space-time adaptive processing (STAP), clutter suppression, convergence, dimension reduction, cyclic iteration

中图分类号:

V243.2

周延, 冯大政, 朱国辉. 空域数据重排的后多普勒自适应处理方法[J]. 航空学报, 2015, 36(9): 3020-3026.

ZHOU Yan, FENG Dazheng, ZHU Guohui. Post-Doppler adaptive processing method based on spatial data rearrangement[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2015, 36(9): 3020-3026.

参考文献

[1] Brennan L E, Reed I S. Theory of adaptive radar[J]. IEEE Transactions on Aerospace and Electronic Systems, 1973, 9(2): 237-252.
[2] Klemm R. Space-time adaptive processing-principles and applications[M]. London: The Institute of Electrical Engineers, 2002: 101-104.
[3] Melvin W L. A STAP overview[J]. IEEE Aerospace and Electronics Systems Magazine, 2004, 21(1): 112-114.
[4] Wang H, Cai L. On adaptive spatial-temporal processing for airborne surveillance radar systems[J]. IEEE Transactions on Aerospace and Electronic Systems, 1994, 30 (3): 660-669.
[5] Haimovich A. The eigencanceler: Adaptive radar by eigenanalysis methods[J]. IEEE Transactions on Aerospace and Electronic Systems, 1996, 32(2): 532-542.
[6] Reed I S, Mallet J D, Brennan L E. Rapid convergence rate in adaptive arrays[J]. IEEE Transactions on Aerospace and Electronic Systems, 1974, 10(6): 853-863.
[7] Haimovich A. Asymptotic distribution of the conditional signal-to-noise ratio in an eigenanalysis-based adaptive array[J]. IEEE Transactions on Aerospace and Electronic Systems, 1997, 33(3): 988-997.
[8] Brown R D, Schneible R A, Wicks M C, et al. STAP for clutter suppression with sum and difference beams[J]. IEEE Transactions on Aerospace and Electronics Systems, 2000, 36 (2): 634-646.
[9] Li J S, Sun J P, Mao S Y. An element error compensation STAP approach based on covariance matrix taper[J]. Acta Aeronautica et Astronautica Sinica, 2009, 30(7): 1292-1297 (in Chinese). 李京生, 孙进平, 毛士艺. 一种基于协方差矩阵加权的阵元误差补偿STAP处理[J]. 航空学报, 2009, 30(7): 1292-1297.
[10] Wang G, Lu Y. Clutter rank of STAP in MIMO radar with waveform diversity[J]. IEEE Transactions on Signal Processing, 2010, 58(2): 938-943.
[11] Aboutanios E, Mulgrew B. Hybrid detection approach for STAP in heterogeneous clutter[J]. IEEE Transactions on Aerospace and Electronic Systems, 2010, 46(3): 1021-1033.
[12] Sun K, Meng H D, Wang Y L, et al. Direct data domain STAP using sparse representation of clutter spectrum[J]. Signal Processing, 2011, 91(9): 2222-2236.
[13] Ginolhac G, Forster P, Pascal F, et al. Performance of two low-rank STAP filters in a heterogeneous noise[J]. IEEE Transactions on Signal Processing, 2013, 61(1): 57-61.
[14] Cao Y, Feng D Z, Shui P L, et al. Space-time adaptive clutter canceller applied to airborne MIMO radar[J]. Acta Aeronautica et Astronautica Sinica, 2013, 34(7): 1654-1662 (in Chinese). 曹杨, 冯大政, 水鹏朗, 等. 机载MIMO雷达空时自适应杂波对消器[J]. 航空学报, 2013, 34(7): 1654-1662.
[15] Tang B, Zhang Y, Li K. Adaptive clutter suppression research based on priori knowledge and its accuracy evaluation[J]. Acta Aeronautica et Astronautica Sinica, 2013, 34(5): 1174-1180 (in Chinese). 唐波, 张玉, 李科. 基于先验知识及其定量评估的自适应杂波抑制研究[J]. 航空学报, 2013, 34(5): 1174-1180.
[16] Ginolhac G, Forster P, Pascal F, et al. Exploiting persymmetry for low-rank space time adaptive processing[J]. Signal Processing, 2014, 97(7): 242-251.
[17] Dippetro R C. Extended factored space-time processing for airborne radar system[C]//Proceedings of the 26th Asilomar Conference on Signals, Systems and Computers, 1992: 425-430.
[18] Bao Z, Liao G S, Wu R B, et al. 2-D temporal-spatial adaptive clutter suppression for phased array airborne radar[J]. Acta Electronica Sinica, 1993, 21(9): 1-7 (in Chinese). 保铮, 廖桂生, 吴仁彪, 等. 相控阵机载雷达杂波抑制的时空二维自适应滤波[J]. 电子学报, 1993, 21(9): 1-7.
[19] Stoica P,Selen Y. Cyclic minimizers, majorization techniques, and the expectation-maximization algorithm: A refresher[J]. IEEE Signal Processing Magazine, 2004, 21(1): 112-114.

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

空域数据重排的后多普勒自适应处理方法

Post-Doppler adaptive processing method based on spatial data rearrangement

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]	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.
[2]	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.
[3]	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.
[4]	马率, 张露, 刘钒, 孙俊峰, 崔兴达. 类X-37B航天器气动力天地相关性数值模拟[J]. 航空学报, 2021, 42(2): 624010-624010.
[5]	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.
[6]	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.
[7]	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.
[8]	胡旭超, 谭贤四, 曲智国, 罗艺, 池鹏飞. 风电场雷达杂波动态重构抑制方法[J]. 航空学报, 2020, 41(1): 323269-323269.
[9]	张永杰, 吴莹莹, 朱胜利, 王斌团, 谭兆光, 袁昌盛. 翼身融合民机典型PRSEUS受压壁板屈曲及渐进损伤分析[J]. 航空学报, 2019, 40(9): 623185-623185.
[10]	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.
[11]	洪俊武, 王运涛, 李伟, 杨小川. HiLiftPW-3高升力构型数值模拟[J]. 航空学报, 2019, 40(3): 122391-122391.
[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]	夏赛强, 向虎, 陈文峰, 杨军, 陈一畅. 基于CEMD的旋翼微动目标杂波抑制方法[J]. 航空学报, 2018, 39(9): 322082-322091.
[15]	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.