UWB SAR遮盖性干扰效果评估及抑制方法研究
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摘要
干扰抑制是超宽带合成孔径雷达(UWB SAR)的关键技术之一。射频干扰(RFI)和噪声干扰是UWB SAR面临的最具代表性的干扰形式,对它们的抑制是UWB SAR干扰抑制的重要内容。本文在理论推导、数据仿真的基础上,分析了原始回波数据在时域、频域和小波变换域的特征以及复图像数据在图像域、图像频域和图像小波变换域的特征,提出了几种行之有效的信号域和图像域抑制方法。
本文首先建立了回波信号和几种典型噪声干扰的模型,分析了不同功率、带宽和类型的噪声干扰对UWB SAR的干扰效果,为后续工作奠定了良好的基础。并形成了基于复图像的评估方法,即以灰度图、信噪比和相关系数来评估干扰效果及后续干扰方法的优劣。
对于RFI和窄带噪声干扰,本文研究了频域陷波和谱均衡两种方法,并将之应用到信号域来抑制窄带干扰。分析了小波包变换域上信号与干扰的差异,在信号域上研究了基于小波包变换的窄带干扰抑制方法;考虑到方法的实时性,进而分析了图像小波包变换域上信号与干扰的差异,提出了在图像域上基于小波包变换窄带干扰抑制方法(NJSIDWPT)。通过实验仿真验证了这些方法的有效性,评估参数结果进一步说明了NJSIDWPT在抑制窄带噪声干扰方面远优于其它的方法。
对于宽带噪声干扰,本文研究了小波包阈值方法,并将之应用到信号域和图像域来抑制宽带噪声干扰。考虑到方法的灵活性,对小波包阈值方法加以改进,提出了基于小波包阈值化和自适应加窗的复图像去噪法(RNCIWPTAW)。经过实验仿真评估,指出了小波包阈值方法在信号域中无效,而RNCIWPTAW有效且性能良好。
Jamming suppression is one of the key techniques of UWB SAR. RFI and noise interferences are the most representative jammings in UWB SAR which receive great considerations in jamming suppression. Based on theoretical deductions and data simulations, this dissertation analyzes properties of echo data in time domain, frequency domain and wavelet packet transform(WPT) domain. We also analysize properties of complex image data in image domain, image frequency domain and image wavelet packet transform domain. Several methods are proposed for jamming suppression in signal domain and image domain respectively.
At first, we build models of echo signal and several typical noise interferences and then analyze effects on UWB SAR by interferences with different power, bandwidth and type. So a good beginning for later work is made. Evaluation method is formed, in which jamming effects and performances of suppression methods can be evaluated by gray image, SNR and correlation coefficient.
For RFI and narrowband noise interferences, this dissertation studies notch filter and spectrum equilibrium and uses them to suppress narrow jammings in signal domain. By analysises on difference between signal and jamming in wavelet packet transform domain, we study methods of narrowband jamming suppression in signal domain based on WPT. Considering the real time feature, and by further analysises on difference between signal and jamming in image wavelet packet transform domain, we propose a method of Narrowband Jamming Suppression in Image Domain based on WPT(NJSIDWPT). The efficiencies of all methods mentioned are validated by simulation experiments and the evaluation result shows that performances of NJSIDWPT on narrowband noise interferences suppression outperform other methods greatly.
For wideband noise interferences, this dissertation studies wavelet packet threshold method and uses it to suppress wideband noise interferences in signal domain and image domain. In order to improve the flexibilities of methods, we propose an approach to Remove Noise from Complex Image based on Wavelet Packet Threholding and Adaptive Windowing(RNCIWPTAW). Evaluating by simulation, we find that wavelet packet theshold method is invalid in signal domain but RNCIWPTAW is valid with fine properties.
本文首先建立了回波信号和几种典型噪声干扰的模型,分析了不同功率、带宽和类型的噪声干扰对UWB SAR的干扰效果,为后续工作奠定了良好的基础。并形成了基于复图像的评估方法,即以灰度图、信噪比和相关系数来评估干扰效果及后续干扰方法的优劣。
对于RFI和窄带噪声干扰,本文研究了频域陷波和谱均衡两种方法,并将之应用到信号域来抑制窄带干扰。分析了小波包变换域上信号与干扰的差异,在信号域上研究了基于小波包变换的窄带干扰抑制方法;考虑到方法的实时性,进而分析了图像小波包变换域上信号与干扰的差异,提出了在图像域上基于小波包变换窄带干扰抑制方法(NJSIDWPT)。通过实验仿真验证了这些方法的有效性,评估参数结果进一步说明了NJSIDWPT在抑制窄带噪声干扰方面远优于其它的方法。
对于宽带噪声干扰,本文研究了小波包阈值方法,并将之应用到信号域和图像域来抑制宽带噪声干扰。考虑到方法的灵活性,对小波包阈值方法加以改进,提出了基于小波包阈值化和自适应加窗的复图像去噪法(RNCIWPTAW)。经过实验仿真评估,指出了小波包阈值方法在信号域中无效,而RNCIWPTAW有效且性能良好。
Jamming suppression is one of the key techniques of UWB SAR. RFI and noise interferences are the most representative jammings in UWB SAR which receive great considerations in jamming suppression. Based on theoretical deductions and data simulations, this dissertation analyzes properties of echo data in time domain, frequency domain and wavelet packet transform(WPT) domain. We also analysize properties of complex image data in image domain, image frequency domain and image wavelet packet transform domain. Several methods are proposed for jamming suppression in signal domain and image domain respectively.
At first, we build models of echo signal and several typical noise interferences and then analyze effects on UWB SAR by interferences with different power, bandwidth and type. So a good beginning for later work is made. Evaluation method is formed, in which jamming effects and performances of suppression methods can be evaluated by gray image, SNR and correlation coefficient.
For RFI and narrowband noise interferences, this dissertation studies notch filter and spectrum equilibrium and uses them to suppress narrow jammings in signal domain. By analysises on difference between signal and jamming in wavelet packet transform domain, we study methods of narrowband jamming suppression in signal domain based on WPT. Considering the real time feature, and by further analysises on difference between signal and jamming in image wavelet packet transform domain, we propose a method of Narrowband Jamming Suppression in Image Domain based on WPT(NJSIDWPT). The efficiencies of all methods mentioned are validated by simulation experiments and the evaluation result shows that performances of NJSIDWPT on narrowband noise interferences suppression outperform other methods greatly.
For wideband noise interferences, this dissertation studies wavelet packet threshold method and uses it to suppress wideband noise interferences in signal domain and image domain. In order to improve the flexibilities of methods, we propose an approach to Remove Noise from Complex Image based on Wavelet Packet Threholding and Adaptive Windowing(RNCIWPTAW). Evaluating by simulation, we find that wavelet packet theshold method is invalid in signal domain but RNCIWPTAW is valid with fine properties.
引文
[01] 张澄波. 综合孔径雷达[M ].北京:科学出版社,1989
[02] 赵国庆. 雷达对抗原理[M ].西安:西安电子科技大学出版社,1999
[03] 黄晓涛. UWB-SAR 抑制 RFI 方法研究. [博士学位论文],长沙:国防科技大学,1999
[04] Bruce H. Ferrell, Interference Suppression in UHF Synthetic-Aperture Radar [ J ], SPIE, 1995, Vol. 2487:96-106
[05] M. Braunstein, J. Ralson and D. Sparrow, Signal processing approaches to radio frequency interference (RFI ) suppression[ J ], SPIE, 1994, Vol. 2230:190-208
[06] T. Miller, J. McCorkle and L. Potter, Near-least-squares radio frequency interference suppression[ J ], SPIE, 1995, Vol. 2487:72-83
[07] A. Golden, Jr., S. A. Werness, et al., Radio frequency interference removal in a VHF/UHF deramp SAR[ J ], SPIE, 1995,Vol. 2487:84-95
[08] K. Abend and J. McCorkle, Radio and TV interference extraction for ultra-wideband radar[ J ], SPIE, 1995,Vol. 2487:119-129
[09] Huang Xiaotao, Zhou Zhimin and Liang Diannong. Effects of RFI on UWB-SAR using LFM waveforms, in IEEE International Conference on Radar, 2001, pp. 631~633.
[10] 黎海涛. 超宽带雷达关键技术研究:[博士学位论文],成都:电子科技大学,2000
[11] 石俊. 对合成孔径雷达干扰方法的研究:[硕士学位论文],西安:西安电子科技大学,2003
[12] 杜贤俊. 合成孔径雷达抗干扰技术研究:[硕士学位论文],成都:电子科技大学,2003
[13] 倪燕. 对合成孔径雷达干扰技术的研究:[硕士学位论文],成都:电子科技大学,2003
[14] 王彦平,彭海良,吴一戎,胡东辉. 合成孔径雷达射频干扰抑制的现状及展望[ J ],航天电子对抗,2002(6):18-24
[15] 王盛利. 合成孔径雷达的有源欺骗干扰方法研究[ J ]. 电子学报,2003,(12):1900-1902
[16] 王兵. 合成孔径雷达的噪声干扰[ J ]. 电子对抗技术,2004,(4):43-46.
[17] 文科,等.合成孔径雷达理论模型下点目标干扰效果评估研究[ J ].无线电通信技术,2002,(6):49-50.
[18] 韩中生. SAR 成像及干扰效果评估方法研究[ J ]. 飞行器测量学报,2004,第 23 卷第 2 期:81-84.
[19] 吴彦鸿,叶伟,刘树贤,等. 噪声干扰的图像特征研究[ J ]. 装备指挥技术学院学报,2002,(13):70-73.
[20] 刘永坦. 雷达成像技术[M ]. 哈尔滨:哈尔滨工业大学出版社,1999
[21] 罗鹏飞,张文明,刘福声. 随机信号分析[M ]. 长沙:国防科技大学出版社,2000.8
[22] 皇甫堪,陈建文,楼生强. 现代数字信号处理[M ]. 北京:电子工业出版社,2003.9
[23] 彭玉华. 小波变换与工程应用[M ]. 北京:科学出版社,1999
[24] 杨福生. 小波变换的工程分析与应用[ M ]. 北京:科学出版社,1999
[25] 赵松年,熊小芸. 子波变换与子波分析[M ]. 北京:电子工业出版社,1996
[26] 陈武凡. 小波分析及其在图像处理中的应用[M ]. 北京:科学出版社,2002
[27] Bin Wang, LiMing Zhang. Automated Removal of Ghost Noise From SAR Images Using Wavelet Packet Transform[ J ], IEEE Trans.on GRS, Vol.41, No. 10, October 2003:2409-2414
[28] Hao Zhou, Biyang Wen, and Shicai Wu. Dense Radio Frequency Interference Suppression in HF Radars[ J ], IEEE SIGNAL PROCESSING LETTERS, VOL. 12, NO. 5, MAY 2005:361-364
[29] Andreas Reigber, Laurent Ferro-Famil. Interference Suppression in Synthesized SAR Images [ J ], IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, VOL. 2, NO. 1, JANUARY 2005:45-49
[30] Lijun Xu. Cancellation of Harmonic Interference by Baseline Shifting of Wavelet Packet Decomposition Coefficients[ J ], IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 53, NO. 1, JANUARY 2005:222-230
[31] E. Pardo, J.J. Pe′rez and M.A. Rodr?′guez. Interference excision in DSSS based on undecimated wavelet packet transform[ J ], IEEE ELECTRONICS LETTERS Vol. 39, No. 21, 16th October 2003:
[32] Hao Deng, Hao Ling. Clutter Reduction for Synthetic Aperture Radar Images Using Adaptive Wavelet Packet Transform[ J ], IEEE 1999:1780-1783
[33] Hyung Jun Kim, Ping Liang. Target Extraction from Clutter Images Using Wavelet Packet Analysis, at the IEEE 1998 National Radar Conference, Dallas, TX, 12-13 May 1998:195-200
[34] 袁俊泉,马晓岩. 基于平均阈值的小波包去噪方法研究[ J ]. 武汉交通科技大学学报,2000(2):215-217.
[35] 郑海波,陈心昭,李志远. 基于小波包变换的一种降噪算法[ J ]. 合肥工业大学学报,2001(4):459-462.
[36] 丁兴号,邓善熙,杨永跃. 基于小波包的图像去噪方法[ J ]. 电子测量与仪器学报,2003(2):35-39.
[37] 庞绍芳,张代英,陈跃宁. 基于小波包分析的能量阈值消噪[ J ]. 辽宁大学学报,2004(2):140-142.
[38] 刘永昌,张平,严卫东,陈华. 小波包阈值法去除合成孔径雷达图像斑点噪声[ J ]. 红外与激光工程,2001(3):160-162.
[39] 鲁怀伟,杜三山. 一种小波包去噪自适应阈值算法[ J ]. 兰州铁道学院学报,2001(6):11-15.
[40] 赵瑞珍. 小波理论及其在图像、信号处理中的算法研究:[博士学位论文],西安:西安电子科技大学,2001
[41] 黄秋元,任晓明,刘炜霞. 一种基于子波包和中值滤波的图像去噪方法[ J ]. 武汉理工大学学报,2003(1):53-55.
[42] 向前,林春生,龚沈光. 基于小波包变换的非高斯噪声信号结构分析[ J ]. 电子与信息学报,2004(1):60-64.
[43] 邓炜,赵荣椿. 基于小波变换的图像相干斑消除方法研究[ J ]. 信号处理,2001(1):86-90.
[02] 赵国庆. 雷达对抗原理[M ].西安:西安电子科技大学出版社,1999
[03] 黄晓涛. UWB-SAR 抑制 RFI 方法研究. [博士学位论文],长沙:国防科技大学,1999
[04] Bruce H. Ferrell, Interference Suppression in UHF Synthetic-Aperture Radar [ J ], SPIE, 1995, Vol. 2487:96-106
[05] M. Braunstein, J. Ralson and D. Sparrow, Signal processing approaches to radio frequency interference (RFI ) suppression[ J ], SPIE, 1994, Vol. 2230:190-208
[06] T. Miller, J. McCorkle and L. Potter, Near-least-squares radio frequency interference suppression[ J ], SPIE, 1995, Vol. 2487:72-83
[07] A. Golden, Jr., S. A. Werness, et al., Radio frequency interference removal in a VHF/UHF deramp SAR[ J ], SPIE, 1995,Vol. 2487:84-95
[08] K. Abend and J. McCorkle, Radio and TV interference extraction for ultra-wideband radar[ J ], SPIE, 1995,Vol. 2487:119-129
[09] Huang Xiaotao, Zhou Zhimin and Liang Diannong. Effects of RFI on UWB-SAR using LFM waveforms, in IEEE International Conference on Radar, 2001, pp. 631~633.
[10] 黎海涛. 超宽带雷达关键技术研究:[博士学位论文],成都:电子科技大学,2000
[11] 石俊. 对合成孔径雷达干扰方法的研究:[硕士学位论文],西安:西安电子科技大学,2003
[12] 杜贤俊. 合成孔径雷达抗干扰技术研究:[硕士学位论文],成都:电子科技大学,2003
[13] 倪燕. 对合成孔径雷达干扰技术的研究:[硕士学位论文],成都:电子科技大学,2003
[14] 王彦平,彭海良,吴一戎,胡东辉. 合成孔径雷达射频干扰抑制的现状及展望[ J ],航天电子对抗,2002(6):18-24
[15] 王盛利. 合成孔径雷达的有源欺骗干扰方法研究[ J ]. 电子学报,2003,(12):1900-1902
[16] 王兵. 合成孔径雷达的噪声干扰[ J ]. 电子对抗技术,2004,(4):43-46.
[17] 文科,等.合成孔径雷达理论模型下点目标干扰效果评估研究[ J ].无线电通信技术,2002,(6):49-50.
[18] 韩中生. SAR 成像及干扰效果评估方法研究[ J ]. 飞行器测量学报,2004,第 23 卷第 2 期:81-84.
[19] 吴彦鸿,叶伟,刘树贤,等. 噪声干扰的图像特征研究[ J ]. 装备指挥技术学院学报,2002,(13):70-73.
[20] 刘永坦. 雷达成像技术[M ]. 哈尔滨:哈尔滨工业大学出版社,1999
[21] 罗鹏飞,张文明,刘福声. 随机信号分析[M ]. 长沙:国防科技大学出版社,2000.8
[22] 皇甫堪,陈建文,楼生强. 现代数字信号处理[M ]. 北京:电子工业出版社,2003.9
[23] 彭玉华. 小波变换与工程应用[M ]. 北京:科学出版社,1999
[24] 杨福生. 小波变换的工程分析与应用[ M ]. 北京:科学出版社,1999
[25] 赵松年,熊小芸. 子波变换与子波分析[M ]. 北京:电子工业出版社,1996
[26] 陈武凡. 小波分析及其在图像处理中的应用[M ]. 北京:科学出版社,2002
[27] Bin Wang, LiMing Zhang. Automated Removal of Ghost Noise From SAR Images Using Wavelet Packet Transform[ J ], IEEE Trans.on GRS, Vol.41, No. 10, October 2003:2409-2414
[28] Hao Zhou, Biyang Wen, and Shicai Wu. Dense Radio Frequency Interference Suppression in HF Radars[ J ], IEEE SIGNAL PROCESSING LETTERS, VOL. 12, NO. 5, MAY 2005:361-364
[29] Andreas Reigber, Laurent Ferro-Famil. Interference Suppression in Synthesized SAR Images [ J ], IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, VOL. 2, NO. 1, JANUARY 2005:45-49
[30] Lijun Xu. Cancellation of Harmonic Interference by Baseline Shifting of Wavelet Packet Decomposition Coefficients[ J ], IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 53, NO. 1, JANUARY 2005:222-230
[31] E. Pardo, J.J. Pe′rez and M.A. Rodr?′guez. Interference excision in DSSS based on undecimated wavelet packet transform[ J ], IEEE ELECTRONICS LETTERS Vol. 39, No. 21, 16th October 2003:
[32] Hao Deng, Hao Ling. Clutter Reduction for Synthetic Aperture Radar Images Using Adaptive Wavelet Packet Transform[ J ], IEEE 1999:1780-1783
[33] Hyung Jun Kim, Ping Liang. Target Extraction from Clutter Images Using Wavelet Packet Analysis, at the IEEE 1998 National Radar Conference, Dallas, TX, 12-13 May 1998:195-200
[34] 袁俊泉,马晓岩. 基于平均阈值的小波包去噪方法研究[ J ]. 武汉交通科技大学学报,2000(2):215-217.
[35] 郑海波,陈心昭,李志远. 基于小波包变换的一种降噪算法[ J ]. 合肥工业大学学报,2001(4):459-462.
[36] 丁兴号,邓善熙,杨永跃. 基于小波包的图像去噪方法[ J ]. 电子测量与仪器学报,2003(2):35-39.
[37] 庞绍芳,张代英,陈跃宁. 基于小波包分析的能量阈值消噪[ J ]. 辽宁大学学报,2004(2):140-142.
[38] 刘永昌,张平,严卫东,陈华. 小波包阈值法去除合成孔径雷达图像斑点噪声[ J ]. 红外与激光工程,2001(3):160-162.
[39] 鲁怀伟,杜三山. 一种小波包去噪自适应阈值算法[ J ]. 兰州铁道学院学报,2001(6):11-15.
[40] 赵瑞珍. 小波理论及其在图像、信号处理中的算法研究:[博士学位论文],西安:西安电子科技大学,2001
[41] 黄秋元,任晓明,刘炜霞. 一种基于子波包和中值滤波的图像去噪方法[ J ]. 武汉理工大学学报,2003(1):53-55.
[42] 向前,林春生,龚沈光. 基于小波包变换的非高斯噪声信号结构分析[ J ]. 电子与信息学报,2004(1):60-64.
[43] 邓炜,赵荣椿. 基于小波变换的图像相干斑消除方法研究[ J ]. 信号处理,2001(1):86-90.