雷达有源欺骗干扰综合感知方法研究
|
摘要
综合电子干扰是雷达的四大威胁之一，特别是随着数字射频存储器（DRFM）技术的产生和应用，由它构成的欺骗干扰机可以产生灵活多样式、对抗性强的多种欺骗干扰，对军用雷达构成了严重的威胁。此外，现有的雷达装备虽然都有一定的抗干扰措施（ECCM），但是由于不具备干扰感知功能，无法根据干扰环境尽快选取最优的抗干扰手段。
为了提高复杂电磁环境下雷达的预警探测能力，本文结合欺骗干扰的产生机理及其对雷达的作用机理，研究雷达有源欺骗干扰的感知方法，为后续的雷达有源欺骗干扰抑制提供先验信息，以便更有针对性地调度雷达抗干扰手段进行雷达反对抗。本文首先分析了干扰的产生机理，然后通过从信号处理、信息处理、波形分集和干扰机指纹特征几个方面研究了欺骗干扰的综合感知方法。论文的主要工作和研究成果如下：
（1）介绍了本文的研究背景，介绍了目前常用的抗干扰方法，对近年来国内外的雷达有源欺骗干扰感知技术研究现状进行了较为全面的综述。介绍欺骗干扰的产生机理和信号模型。首先介绍了DRFM欺骗干扰的产生机理，并进行了DRFM欺骗干扰的特性分析，然后介绍了基于干扰过程的拖引干扰的产生机理，主要包括距离拖引干扰、速度拖引干扰和距离-速度联合拖引干扰，最后研究了其它类型的欺骗干扰。根据干扰的产生机理提出了欺骗干扰的模型，为后面干扰感知算法研究奠定了基础。
（2）通过干扰的作用过程建立针对跟踪雷达的典型拖引欺骗干扰的信号模型，利用多尺度分解理论进行欺骗干扰的感知算法研究。提出了基于小波分解和基于经验模式分解的欺骗干扰感知算法。第一种算法中利用小波分解得到高频细节分量和低频逼近分量，提取各阶分解向量的能量比作为特征参数，从而实现各种拖引干扰的识别和分类。第二种算法处理流程和前一种方法类似，通过经验模式分解得到本征模式函数分量，提取分解分量的特征参数实现三类欺骗干扰的感知。
（3）通过频域和慢时域二维联合处理，提取二维积谱的非负矩阵分解向量特征和二维频谱的纹理特征，进行拖引干扰的识别。首先建立频域和慢时域的二维积谱矩阵，利用非负矩阵分解理论，提取分解矩阵中各阶向量的特征参数，用于欺骗干扰的感知。将图像处理中的纹理特征引入到欺骗干扰的感知算法中，提取二维频谱灰度图像的纹理特征进行欺骗干扰的感知。
（4）通过信息域进行欺骗干扰的存在性检测，提出了2种基于幅度起伏特性的欺骗干扰感知算法，包括基于拟合优度的欺骗干扰检测算法和基于粒子滤波的欺骗干扰检测算法。第一种算法通过分析干扰机在释放干扰时雷达接收波束内的信号幅度起伏差异，建立了欺骗干扰存在性的检测流程，提出了两种拟合优度的欺骗干扰检测算法，并通过仿真比较了各种条件下的Anderson-Darling（AD）检测和修正的AD（MAD）检测算法的性能。第二种算法利用拖引干扰在捕获期内，目标与干扰的在同一个波束内不可分辨，导致接收信号混叠到相邻匹配滤波采样点，基于这一特性建立了欺骗干扰的信号模型，提出了基于似然比的检测流程，通过粒子滤波检测器实现了欺骗干扰的检测。
（5）研究了基于波形分集理论的欺骗干扰感知算法，包括基于随机线性调频斜率的波形分集信号的欺骗干扰感知算法和基于混沌调相波形分集信号的欺骗干扰感知算法。针对线性调频信号和相位编码信号，分别采用广义似然比检测（GLRT）算法和Holder系数的特征提取方法，对欺骗干扰的检测和识别性能进行了数字仿真验证。
（6）针对欺骗干扰在生成过程中干扰机存在二次调制，利用Volterra模型建立干扰机的非线性失真模型，提取了干扰机的功放指纹特征，研究了基于子空间和基于粒子群优化稀疏分解方法的欺骗干扰识别方法。
With the generation and applicationof the digital radio frequency memory (DRFM)technology, the synthetical electronic counter measure (ECM) is one of the so-called“four threats” to the radar.The deception jammer consists of the DRFM, which cangenerate multiple modes, fleasibility and stronger opposability jamming. It forms themost severe threat to military radar. Moreover, although the existing radars are equippedwith some electronic counter-countermeasures (ECCM), they cannot choose theoptimum anti-jamming measurement automatically according to the jammingenvironment, as a result of the absence of the jamming mode sensing function.
In order to enhance the radar early-warning and detecting performance in thecomplicated electromagnetic environment, the generation mechanism of jamming andthe mechanism of jamming on radar are studied. On the bases, the sensing methods ofactive deception jamming are researched, which can provid the priori information forthe subsequent radar deception jamming suppression. Then the radar will choose thebest ECCM methods against the decptive jamming.First, the generation mechanism ofthe deception jamming is analyzes detailedly.Then the deception jamming integratedsensing algorithms are studied from the signal processing, information processing,waveform diversity and fingerprint characteristics of the deceptive jammer. The maincontents and results are listed as follows.
(1) The research background is ascertained, and the conventional ECCM isintroduced. The domestic and overseas research status of the radar active deceptionjamming sensing methods is addressed detailedly. Firstly, the generation mechanism ofthe radar deception jamming based on DRFM is introduced, and then the generationmechanism of the pull jamming based on the process is presented, including range gatepull jamming, velocity gate pull jammingand range-velocity gate pull jamming. Finally,other type of deception jamming is studied. The deception jamming model is thefoundation forthe further jamming sensing algorithms.
(2) The typical gate pull deception jamming signal model of the tracking radar isestablished in the releasing process of the jamming, multi-scale decomposition theory isused to study the sensing algorithm of deception jamming. Two types of multi-scaledecomposition methods of deception jamming sensing algorithms are proposed, including those based on wavelet decomposition algorithm and an algorithm based onempirical mode decomposition. In the first algorithm, wavelet decomposition of thenormalized radar received signal is used to get the high-frequency detail componentsand the low-frequency approximation components. Normalized power ratio is extractedas the multi-scale decomposition coefficients of the radar received signal. Base on thoseabove, the identification algorithm of the three towing interference is achieved. In thesecond algorithm, the processing method is similar to the former. The intrinsic modefunction (IMF) components are derived directly from the empirical modedecomposition. The features of the decomposed components are extracted to achieve thesensing algorithm of three types of jamming.
(3) Non-negative matrix factorization (NMF) vector characteristics of productspectrum and texture characteristic parameters of two-dimensional spectrum areextracted by joint frequency domain and slow-time domain processing. Based on these,identification algorithms of pull jamming are proposed. In the first algorithm, productspectrum matrix (PSM) of the frequency domain and slow-time domain is established atthe beginning. Then, NMF theory is applied to the PSM, and features are extracted fromeach vectors of the decomposed matrx. Finally, a deception jamming sensing algorithmis proposed. In the second algorithm, the texture features of image processing areintroduced into deception jamming sensing algorithm. The gray image texturecharacteristics of two-dimensional spectrum are extracted. The sensing algorithm ofdeception jamming is presented using texture parameters.
(4) Detection algorithms of the presence of deception jamming based oninformation domain processing are proposed, which are two kinds of deceptionjamming sensing algorithms based on amplitude fluctuation features perception. Thedetection algorithms are the goodness of fit (GOF) and particle filter (PF), respectively.In the first algorithm, when the deceptive jamming appears, the amplitude fluctuation ofthe received signal within the radar beam is different from echo. The existence ofdeception jamming detection is established, and two types of GOF detection algorithmsare proposed. Finally, the performance of Anderson-Darling (AD) detection andmodified Anderson-Darling (MAD) detection is compared by the simulationexperiments under different conditions. In the second algorithm, the echo and jammingwithin the same beam is unresolved in the pull jamming capture period. Consideringthat the energy of received signal will spill over to adjacent matched filter sampling points, the signal model is established. Base on those above, a likelihood ratio testmodel is developed. Finally, the detection algorithms of the presence of pull jammingare implemented, which uses particle filterdetector.
(5) The sensing algorithms of deception jamming based on the waveform diversitytheory is studied, including those of random linear frequency modulate ratio signal(RLFMR) and chaotic phase modulation (CPM) signal. For linear frequency modulate(LFM) signal and the phase-coded signal, the generalized likelihood ratio test (GLRT)algorithm and Holder coefficient feature extraction method are presented, respectively.The detection and identification performance for deceptive jamming is verified bynumerical simulation.
(6) Based on the second modulation of jammers in the deception jamminggeneration process, the nonlinear distortion model of jammer is established usingVolterra model. The fingerprint feature of jammer is extracted. The identificationmethod of deception jamming is studied based on subspace and particle swarmoptimization (PSO) in sparse decomposition method.
为了提高复杂电磁环境下雷达的预警探测能力，本文结合欺骗干扰的产生机理及其对雷达的作用机理，研究雷达有源欺骗干扰的感知方法，为后续的雷达有源欺骗干扰抑制提供先验信息，以便更有针对性地调度雷达抗干扰手段进行雷达反对抗。本文首先分析了干扰的产生机理，然后通过从信号处理、信息处理、波形分集和干扰机指纹特征几个方面研究了欺骗干扰的综合感知方法。论文的主要工作和研究成果如下：
（1）介绍了本文的研究背景，介绍了目前常用的抗干扰方法，对近年来国内外的雷达有源欺骗干扰感知技术研究现状进行了较为全面的综述。介绍欺骗干扰的产生机理和信号模型。首先介绍了DRFM欺骗干扰的产生机理，并进行了DRFM欺骗干扰的特性分析，然后介绍了基于干扰过程的拖引干扰的产生机理，主要包括距离拖引干扰、速度拖引干扰和距离-速度联合拖引干扰，最后研究了其它类型的欺骗干扰。根据干扰的产生机理提出了欺骗干扰的模型，为后面干扰感知算法研究奠定了基础。
（2）通过干扰的作用过程建立针对跟踪雷达的典型拖引欺骗干扰的信号模型，利用多尺度分解理论进行欺骗干扰的感知算法研究。提出了基于小波分解和基于经验模式分解的欺骗干扰感知算法。第一种算法中利用小波分解得到高频细节分量和低频逼近分量，提取各阶分解向量的能量比作为特征参数，从而实现各种拖引干扰的识别和分类。第二种算法处理流程和前一种方法类似，通过经验模式分解得到本征模式函数分量，提取分解分量的特征参数实现三类欺骗干扰的感知。
（3）通过频域和慢时域二维联合处理，提取二维积谱的非负矩阵分解向量特征和二维频谱的纹理特征，进行拖引干扰的识别。首先建立频域和慢时域的二维积谱矩阵，利用非负矩阵分解理论，提取分解矩阵中各阶向量的特征参数，用于欺骗干扰的感知。将图像处理中的纹理特征引入到欺骗干扰的感知算法中，提取二维频谱灰度图像的纹理特征进行欺骗干扰的感知。
（4）通过信息域进行欺骗干扰的存在性检测，提出了2种基于幅度起伏特性的欺骗干扰感知算法，包括基于拟合优度的欺骗干扰检测算法和基于粒子滤波的欺骗干扰检测算法。第一种算法通过分析干扰机在释放干扰时雷达接收波束内的信号幅度起伏差异，建立了欺骗干扰存在性的检测流程，提出了两种拟合优度的欺骗干扰检测算法，并通过仿真比较了各种条件下的Anderson-Darling（AD）检测和修正的AD（MAD）检测算法的性能。第二种算法利用拖引干扰在捕获期内，目标与干扰的在同一个波束内不可分辨，导致接收信号混叠到相邻匹配滤波采样点，基于这一特性建立了欺骗干扰的信号模型，提出了基于似然比的检测流程，通过粒子滤波检测器实现了欺骗干扰的检测。
（5）研究了基于波形分集理论的欺骗干扰感知算法，包括基于随机线性调频斜率的波形分集信号的欺骗干扰感知算法和基于混沌调相波形分集信号的欺骗干扰感知算法。针对线性调频信号和相位编码信号，分别采用广义似然比检测（GLRT）算法和Holder系数的特征提取方法，对欺骗干扰的检测和识别性能进行了数字仿真验证。
（6）针对欺骗干扰在生成过程中干扰机存在二次调制，利用Volterra模型建立干扰机的非线性失真模型，提取了干扰机的功放指纹特征，研究了基于子空间和基于粒子群优化稀疏分解方法的欺骗干扰识别方法。
With the generation and applicationof the digital radio frequency memory (DRFM)technology, the synthetical electronic counter measure (ECM) is one of the so-called“four threats” to the radar.The deception jammer consists of the DRFM, which cangenerate multiple modes, fleasibility and stronger opposability jamming. It forms themost severe threat to military radar. Moreover, although the existing radars are equippedwith some electronic counter-countermeasures (ECCM), they cannot choose theoptimum anti-jamming measurement automatically according to the jammingenvironment, as a result of the absence of the jamming mode sensing function.
In order to enhance the radar early-warning and detecting performance in thecomplicated electromagnetic environment, the generation mechanism of jamming andthe mechanism of jamming on radar are studied. On the bases, the sensing methods ofactive deception jamming are researched, which can provid the priori information forthe subsequent radar deception jamming suppression. Then the radar will choose thebest ECCM methods against the decptive jamming.First, the generation mechanism ofthe deception jamming is analyzes detailedly.Then the deception jamming integratedsensing algorithms are studied from the signal processing, information processing,waveform diversity and fingerprint characteristics of the deceptive jammer. The maincontents and results are listed as follows.
(1) The research background is ascertained, and the conventional ECCM isintroduced. The domestic and overseas research status of the radar active deceptionjamming sensing methods is addressed detailedly. Firstly, the generation mechanism ofthe radar deception jamming based on DRFM is introduced, and then the generationmechanism of the pull jamming based on the process is presented, including range gatepull jamming, velocity gate pull jammingand range-velocity gate pull jamming. Finally,other type of deception jamming is studied. The deception jamming model is thefoundation forthe further jamming sensing algorithms.
(2) The typical gate pull deception jamming signal model of the tracking radar isestablished in the releasing process of the jamming, multi-scale decomposition theory isused to study the sensing algorithm of deception jamming. Two types of multi-scaledecomposition methods of deception jamming sensing algorithms are proposed, including those based on wavelet decomposition algorithm and an algorithm based onempirical mode decomposition. In the first algorithm, wavelet decomposition of thenormalized radar received signal is used to get the high-frequency detail componentsand the low-frequency approximation components. Normalized power ratio is extractedas the multi-scale decomposition coefficients of the radar received signal. Base on thoseabove, the identification algorithm of the three towing interference is achieved. In thesecond algorithm, the processing method is similar to the former. The intrinsic modefunction (IMF) components are derived directly from the empirical modedecomposition. The features of the decomposed components are extracted to achieve thesensing algorithm of three types of jamming.
(3) Non-negative matrix factorization (NMF) vector characteristics of productspectrum and texture characteristic parameters of two-dimensional spectrum areextracted by joint frequency domain and slow-time domain processing. Based on these,identification algorithms of pull jamming are proposed. In the first algorithm, productspectrum matrix (PSM) of the frequency domain and slow-time domain is established atthe beginning. Then, NMF theory is applied to the PSM, and features are extracted fromeach vectors of the decomposed matrx. Finally, a deception jamming sensing algorithmis proposed. In the second algorithm, the texture features of image processing areintroduced into deception jamming sensing algorithm. The gray image texturecharacteristics of two-dimensional spectrum are extracted. The sensing algorithm ofdeception jamming is presented using texture parameters.
(4) Detection algorithms of the presence of deception jamming based oninformation domain processing are proposed, which are two kinds of deceptionjamming sensing algorithms based on amplitude fluctuation features perception. Thedetection algorithms are the goodness of fit (GOF) and particle filter (PF), respectively.In the first algorithm, when the deceptive jamming appears, the amplitude fluctuation ofthe received signal within the radar beam is different from echo. The existence ofdeception jamming detection is established, and two types of GOF detection algorithmsare proposed. Finally, the performance of Anderson-Darling (AD) detection andmodified Anderson-Darling (MAD) detection is compared by the simulationexperiments under different conditions. In the second algorithm, the echo and jammingwithin the same beam is unresolved in the pull jamming capture period. Consideringthat the energy of received signal will spill over to adjacent matched filter sampling points, the signal model is established. Base on those above, a likelihood ratio testmodel is developed. Finally, the detection algorithms of the presence of pull jammingare implemented, which uses particle filterdetector.
(5) The sensing algorithms of deception jamming based on the waveform diversitytheory is studied, including those of random linear frequency modulate ratio signal(RLFMR) and chaotic phase modulation (CPM) signal. For linear frequency modulate(LFM) signal and the phase-coded signal, the generalized likelihood ratio test (GLRT)algorithm and Holder coefficient feature extraction method are presented, respectively.The detection and identification performance for deceptive jamming is verified bynumerical simulation.
(6) Based on the second modulation of jammers in the deception jamminggeneration process, the nonlinear distortion model of jammer is established usingVolterra model. The fingerprint feature of jammer is extracted. The identificationmethod of deception jamming is studied based on subspace and particle swarmoptimization (PSO) in sparse decomposition method.
引文
[1] M. I. Skolnik. Radar handbook3rd Ed[M]. New York: McGraw-Hill,2008
[2]赵国庆.雷达对抗原理[M].西安:西安电子科技大学出版社,1999
[3] A. J. Elbirt. Information warfare: are you at risk?[J]. Technology and Society Magazine, IEEE,2003,22(4):13-19
[4] S. L. Johnston. Radar electronic counter-countermeasures[J]. Aerospace and Electronic Systems,IEEE Transactions on,1978,14(1):109-117
[5] R. Schroer. Electronic warfare.[A century of powered flight:1903-2003][J]. Aerospace and ElectronicSystems Magazine, IEEE,2003,18(7):49-54
[6] N. Li, Y. Zhang. A survey of radar ECM and ECCM[J]. Aerospace and Electronic Systems, IEEETransactions on,1995,31(3):1110-1120
[7] J. Guo, J. Li, Q. Lv. Survey on radar ECCM methods and trends in its developments[C]. Radar,2006.CIE '06. International Conference on, Shanghai,2006,1-4
[8]施龙飞.雷达极化抗干扰技术研究[D].长沙:国防科学技术大学,2007
[9] G. W. Stimson. Introduction to airborne radar[M]. New Jersey, USA: SciTech Pub.,1998
[10] S. A. Vakin, L. N. Shustov, R. H. Dunwell. Fundamentals of electronic warfare[M]. Boston: ArtechHouse,2001
[11] R. M. Davis, R. L. Fante, T. P. Guella, et al. Interference suppression via operating frequencyselection[J]. Antennas and Propagation, IEEE Transactions on,1999,47(4):637-645
[12] M. Soumekh. SAR-ECCM using phase-perturbed LFM chirp signals and DRFM repeat jammerpenalization[J]. Aerospace and Electronic Systems, IEEE Transactions on,2006,42(1):191-205
[13] J. Akhtar. An ECCM scheme for orthogonal independent range-focusing of real and false targets[C].Radar Conference,2007IEEE, Boston, MA,2007,846-849
[14] J. Akhtar. Orthogonal block coded ECCM schemes against repeat radar jammers[J]. Aerospace andElectronic Systems, IEEE Transactions on,2009,45(3):1218-1226
[15] J. Akhtar. Removal of range ambiguities with orthogonal block coding techniques[J]. Circuits,Systems, and Signal Processing,2010,29(2):311-330
[16] J. Schuerger, D. Garmatyuk. Performance of random OFDM radar signals in deception jammingscenarios[C]. Radar Conference,2009IEEE, Pasadena, CA, IEEE,2009,1-6
[17] F. Kural, Y. Ozkazanc. A method for detecting RGPO/VGPO jamming[C]. Signal Processing andCommunications Applications Conference,2004,237-240
[18] H. H. M. Ghouz, F. I. A. Elghany, M. M. Qutb. Adaptive space-time processing for interferencesuppression in phased array radar systems. I. Search radar[C]. Radio Science Conference,2000.17th NRSC '2000. Seventeenth National, Minufiya,2000,1-8
[19] H. H. M. Ghouz, F. I. A. Elghany, M. M. Qutb. Adaptive space-time processing for interferencesuppression in phased array radar systems. II. Tracking radar[C]. Radio Science Conference,2000.17th NRSC '2000. Seventeenth National, Minufiya,2000,91-97
[20] Y. Kai-Bor, D. J. Murrow. Adaptive digital beamforming for angle estimation in jamming[J].Aerospace and Electronic Systems, IEEE Transactions on,2001,37(2):508-523
[21] W. R. Blanding, W. Koch, U. Nickel. Adaptive phased-array tracking in ECM using negativeinformation[J]. Aerospace and Electronic Systems, IEEE Transactions on,2009,45(1):152-166
[22] D. S. Garmatyuk, R. M. Narayanan. ECCM capabilities of an ultrawideband bandlimited randomnoise imaging radar[J]. Aerospace and Electronic Systems, IEEE Transactions on,2002,38(4):1243-1255
[23] L. Rosenberg, D. Gray. Anti-jamming techniques for multichannel SAR imaging[J]. Radar, Sonarand Navigation, IEE Proceedings-,2006,153(3):234-242
[24] P. Stavroulakis, N. Farsaris, T. D. Xenos. Anti-jamming transmitter independent radar networks[C].Signal Processing, Communications and Networking,2008. ICSCN '08. International Conferenceon, Chennai,2008,269-273
[25]贲德.机载脉冲多普勒(PD)雷达的工作特点及抗干扰措施[J].现代雷达,2000,22(4):1-6
[26]张光义.提高雷达系统抗干扰能力的一些措施[J].现代雷达,2001,23(1):6-12
[27]常宇亮.瞬态极化雷达测量、检测与抗干技术研究[D].长沙:国防科学技术大学,2010
[28]刘勇.动态目标极化特性测量与极化雷达抗干扰新方法研究[D].长沙:国防科学技术大学,2011
[29]周万幸.一种新型极化抗干扰技术研究[J].电子学报,2009,37(3):454-458
[30]宋立众，乔晓林，吴群.一种弹载相控阵雷达及其极化滤波方法[J].电波科学学报,2009,24(06):1071-1077
[31]宋立众，乔晓林，吴群.一种基于极化DBF的制导雷达抗干扰方法[J].电波科学学报,2010,25(01):109-116
[32]宋立众，乔晓林，吴群.一种极化分集制导雷达及低截获概率信号设计[J].系统工程与电子技术,2009,31(12):2853-2858
[33]张新相，吴铁平，陈天麒.随机信号雷达抗干扰性能分析[J].电波科学学报,2008,23(01):189-194
[34]冯祥芝，许小剑.随机线性调频斜率SAR抗欺骗干扰方法研究[J].系统工程与电子技术,2009,31(01):69-73
[35]冯祥芝，许小剑.混沌码正交频分复用SAR抗干扰能力研究[J].系统仿真学报,2009,21(22):7359-7362
[36]张劲东.自适应雷达系统中波形分集技术的研究[D].南京:南京理工大学,2010
[37]张劲东，李彧晟，朱晓华.基于波形分集的雷达抗欺骗干扰[J].数据采集与处理,2010,25(02):138-142
[38] J. Zhang, D. Zhu, G. Zhang. New antivelocity deception jamming technique using pulses withadaptive initial phases[J]. Aerospace and Electronic Systems, IEEE Transactions on,2013,49(2):1290-1300
[39]郑远，胡英辉，邓云凯.混沌调频雷达成像与欺骗干扰分析[J].系统工程与电子技术,2009,31(05):1071-1074
[40]郑远，胡英辉，邓云凯.混沌相位编码信号成像与反欺骗干扰仿真[J].系统仿真学报,2008,20(15):3962-3965
[41] Y. Deng, Y. Hu, X. Geng. Hyper chaotic logistic phase coded signal and its sidelobe suppression[J].Aerospace and Electronic Systems, IEEE Transactions on,2010,46(2):672-686
[42]谢春健，郭陈江，许家栋.调频率正负交替变化的SAR成像及抗欺骗干扰方法[J].计算机应用,2010,30(05):1383-1389
[43]谢春健，郭陈江，许家栋.基于混沌信号的SAR抗距离向相干干扰方法[J].计算机仿真,2010,27(11):132-135
[44]谢春健，李建周，郭陈江，等.基于Logistic混沌映射移频的SAR转发干扰方法[J].系统工程与电子技术,2011,33(10):2210-2216
[45] G. Lu, B. Tang, G. Gui. Deception ECM signals cancellation processor with joint time-frequencypulse diversity[J]. IEICE Electronics Express,2011,8(19):1608-1613
[46]卢刚.雷达有源假目标抑制方法研究[D].成都:电子科技大学,2012
[47] G. Lu, B. Tang. Deception jammer rejection using pulse diversity in joint slow/fast-time domain[J].Journal of the Chinese Institute of Engineers,2013,36(3):405-410
[48] G. Lu, S. Liao, S. Luo, et al. Cancellation of complicated DRFM range false targets via temporalpulse diversity[J]. Progress In Electromagnetics Research,2010,16:69-84
[49]张淑宁，赵惠昌.伪码引信抗欺骗干扰的互相关正交投影联合法[J].南京理工大学学报(自然科学版),2007,31(04):509-513
[50]张淑宁，赵惠昌，熊刚.基于延时变化量估计的伪码引信抗欺骗式干扰方法[J].宇航学报,2008,29(1):326-330
[51]杨莘元，程万翔，姜弢，等.自适应零点形成技术抑制雷达相干干扰[J].哈尔滨工程大学学报,1999,20(4):69-73
[52]白渭雄，张文，苗淼.旁瓣干扰对抗技术研究[J].系统工程与电子技术,2009,31(1):86-90
[53]张子敬，张浩.校正谱分析在导引头抗干扰中的应用[J].西安电子科技大学学报,1997(S1):96-102
[54]张子敬，张浩，吴洹.抗速度门拖引的解线性调频方法[J].西安电子科技大学学报,1996,23(02):211-217
[55]陈浩，何明浩，毛五星.小波分解在雷达抗速度欺骗干扰中的运用[J].空军雷达学院学报,2006,20(1):31-33
[56] M. H. Sun, B. Tang. Suppression of smeared spectrum ECM signal[J]. Journal of the ChineseInstitute of Engineers,2009,32(3):407-413
[57]孙闽红.雷达抗有源欺骗式干扰算法研究[D].成都:电子科技大学,2008
[58]罗双才，唐斌.一种基于盲分离的欺骗干扰抑制算法[J].电子与信息学报,2011,33(12):2801-2806
[59]罗双才，唐斌.一种空域-极化域联合的雷达欺骗干扰抑制算法[J].信号处理,2012,28(3):443-448
[60]卢刚，唐斌，罗双才. LFM雷达中DRFM假目标自适应对消方法[J].系统工程与电子技术,2011,33(08):1760-1764
[61] G. Lu, D. Zeng, B. Tang. Anti-jamming filtering for DRFM repeat jammer based on stretchprocessing[C]. Signal Processing Systems (ICSPS),20102nd International Conference on,2010,78-82
[62] G. Lu, S. Luo, H. Gu, et al. Adaptive biased weight-based RGPO/RGPI ECCM algorithm[C]. Radar(Radar),2011IEEE CIE International Conference on, Chengdu, IEEE,2011,1067-1070
[63]朱良，曹鹏，禹卫东.基于移频干扰的成像算法抗干扰性能分析[J].电子学报,2011(S1):47-51
[64]李江源，王建国.利用复杂调制LFM信号的SAR抗欺骗干扰技术[J].电子与信息学报,2008,30(9):2111-2114
[65]李云涛，陈永光，贾鑫，等.多载频MIMO-SAR对消处理抗欺骗干扰[J].电子学报,2012,40(9):1790-1794
[66]唐波，王卫延.干涉合成孔径雷达抗干扰性能分析[J].电子与信息学报,2006,28(10):1809-1811
[67]李侠，蔡万勇，花良发，等.责任区雷达组网系统抗干扰优化部署算法[J].系统工程与电子技术,2007,29(8):1254-1257
[68]徐海全，王国宏，关成斌.远距离支援干扰下的目标跟踪技术[J].北京航空航天大学学报,2011,37(11):1353-1358
[69]徐海全，王国宏，关成斌.分布式干扰下雷达网的目标跟踪技术[J].兵工学报,2011,32(6):764-769
[70]刘兆磊，王国宏，张光义，等.机载火控雷达距离拖引目标的交互式多模型跟踪方法[J].航空学报,2005,26(4):465-469
[71]李世忠，王国宏，吴巍，等.分布式干扰下组网雷达目标检测与跟踪技术[J].系统工程与电子技术,2012,34(4):782-788
[72] M. Ahmed. Parameterized DRFM modulator for ECM Systems[J]. International Journal ofAdvanced Electronics and Communication Systems,2012,1(1):56-60
[73] C. M. Kwak. Application of DRFM in ECM for pulse type radar[C]. Infrared, Millimeter, andTerahertz Waves,2009. IRMMW-THz2009.34th International Conference on, Busan,2009,1-2
[74] K. Olivier, J. E. Cilliers, M. du Plessis. Design and performance of wideband DRFM for radar testand evaluation[J]. Electronics letters,2011,47(14):824-825
[75] C. J. Hill, V. Truffert. Statistical processing techniques for detecting DRFM repeat-jam radarsignals[C]. Signal Processing Techniques for Electronic Warfare, IEE Colloquium on, London,1992,1-6
[76] W. D. Blair, M. Brandt-Pearce. Discrimination of target and RGPO echoes using frequencydiversity[C]. System Theory,1997., Proceedings of the Twenty-Ninth Southeastern Symposium on,Cookeville, TN,1997,509-513
[77] P. R. Kalata, T. A. Chmielewski. Range gate pull off (RGPO): detection, observability and α-βtarget tracking[C]. System Theory,1997, Proceedings of the Twenty-Ninth SoutheasternSymposium on, Cookeville, TN,1997,505-508
[78] W. D. Blair, G. A. Watson, T. Kirubarajan, et al. Benchmark for radar allocation and tracking inECM[J]. Aerospace and Electronic Systems, IEEE Transactions on,1998,34(4):1097-1114
[79] T. Kirubarajan, Y. Bar-Shalom, W. D. Blair, et al. IMMPDAF for radar management and trackingbenchmark with ECM[J]. Aerospace and Electronic Systems, IEEE Transactions on,1998,34(4):1115-1134
[80] X. R. Li, B. Slocumband, W. Phillip. Tracking in the presence of range deception ECM and clutterby decomposition and fusion[C]. SPIE Conference on Signal and Data Processing of Small Targets,Denver, Colorado, USA, Society of Photo-Optical Instrumentation Engineers,1999,198-210
[81] V. Behar, C. Kabakchiev, X. R. Li. Excision techniques for reduction of the flow of the RGPO whensolving the benchmark problem[C]. Radar Conference,2000. The Record of the IEEE2000International, Alexandria, VA,2000,862-866
[82] S. D. Berger. Digital radio frequency memory linear range gate stealer spectrum[J]. Aerospace andElectronic Systems, IEEE Transactions on,2003,39(2):725-735
[83] S. D. Berger. The spectrum of a digital radio frequency memory linear range gate stealer electronicattack signal[C]. Radar Conference,2001. Proceedings of the2001IEEE, Atlanta, GA,2001,27-30
[84] M. Greco, F. Gini, A. Farina. Combined effect of phase and RGPO delay quantization on jammingsignal spectrum[C]. Radar Conference,2005IEEE International,2005,37-42
[85] M. Greco, F. Gini, A. Farina, et al. Effect of phase and range gate pull-off delay quantisation onjammer signal[J]. Radar, Sonar and Navigation, IEE Proceedings-,2006,153(5):454-459
[86] M. Greco, F. Gini, A. Farina. Radar detection and classification of jamming signals belonging to acone class[J]. Signal Processing, IEEE Transactions on,2008,56(5):1984-1993
[87] F. Bandiera, A. Farina, D. Orlando, et al. Detection algorithms to discriminate between radar targetsand ECM signals[J]. Signal Processing, IEEE Transactions on,2010,58(12):5984-5993
[88] B. Tao. An ECCM model and the technical development trends to the demands of the future EWcombat[J]. Aerospace and Electronic Systems Magazine, IEEE,1994,9(6):12-16
[89]保铮，谢维信，朱宾.雷达系统抗欺骗型干扰性能的测度[J].电子学报,1989,17(06):13-20
[90]贾鑫，郭桂蓉，梁泰基.一种雷达干扰信号识别的映射统计方法及其实验研究[J].指挥技术学院学报,1994,5(02):14-17
[91]贾鑫，梁泰基，郭桂蓉.一种基于雷达视频波形的噪声调频干扰带宽辨识算法的研究[J].电子学报,1991,19(04):116-119
[92]赵雪飞，赵川，刘峥. PD雷达抗距离-速度同步拖引干扰的频谱识别法[J].雷达与对抗,2005(03):21-24
[93]吕强，李建勋，秦江敏，等.基于神经网络的雷达抗转发式距离欺骗干扰方法[J].系统工程与电子技术,2005,27(2):240-243
[94]李建勋，秦江敏，马晓岩.雷达抗应答式欺骗干扰中的特征提取研究[J].空军雷达学院学报,2004,18(2):4-7
[95]李建勋，秦江敏，马晓岩.基于神经网络的雷达抗应答式欺骗干扰方法[J].空军雷达学院学报,2003,17(4):19-21
[96]李建勋，唐斌，吕强.双谱特征提取在欺骗式干扰方式识别中的应用[J].电子科技大学学报,2009,38(3):329-332
[97]户锋刚，阮怀林，曾昭勇.对距离-速度欺骗干扰的识别方法[J].电子信息对抗技术,2007,22(3):36-39
[98]张红昌，阮怀林.基于支持向量机的雷达欺骗性干扰类型识别[J].火控雷达技术,2009,38(3):17-21
[99]陈建春，耿富录.基于线性预测滤波的抗速度欺骗干扰技术[J].系统工程与电子技术,2002,24(2):22-24
[100]陈建春.速度拖引干扰的频谱识别技术[J].火控雷达技术,1998,27(3):37-42
[101]张翼飞，胡林华，董云龙.一种有效识别速度欺骗干扰的方法[J].空军雷达学院学报,2009,23(3):181-183
[102]张善文，赵栓堂，等.速度拖引干扰下运动目标检测[J].系统工程与电子技术,2001,23(5):57-59
[103]常成.雷达欺骗式干扰检测与实现[D].上海:上海交通大学,2009
[104]熊伟，曹兰英，郝志梅.基于多尺度相像系数的雷达干扰类型频域识别[J].计算机仿真,2010,27(3):19-22
[105]孙闽红，唐斌.距离-速度同步拖引欺骗干扰的频谱特征分析[J].系统工程与电子技术,2009,31(1):83-85
[106]孙闽红，唐斌.基于原子分解理论的雷达欺骗式干扰信号特征提取[J].电波科学学报,2008,23(3):550-554
[107]范伟.雷达有源干扰信号特征分析与识别算法研究[D].成都:电子科技大学,2007
[108]刘旻.雷达复合干扰信号特征提取及智能识别算法研究[D].电子科技大学,2008
[109]熊英，刘旻，唐斌，等.基于盒维数与LZ复杂度的雷达复合干扰特征提取方法[J].数据采集与处理,2008,23(6):663-667
[110]顾海燕.距离-速度有源雷达干扰建模与对抗方法研究[D].成都:电子科技大学,2011
[111]李永平，卢刚，田晓，等.基于模糊函数的SMSP和C＆I干扰识别算法[J].航空兵器,2011(4):51-54
[112] Y. Li, Y. Xiong, B. Tang. SMSP jamming identification based on matched signal transform[C].Computational Problem-Solving (ICCP),2011International Conference on, Chengdu, IEEE,2011,182-185
[113]王涛.弹道中段目标极化域特征提取与识别[D].长沙:国防科学技术大学,2006
[114]王涛，王雪松，刘进，等.干扰背景下瞬时极化测量雷达的目标识别预处理技术[J].电子与信息学报,2008,30(10):2333-2337
[115]王涛，王雪松，肖顺平.随机调制单极化有源假目标的极化鉴别研究[J].自然科学进展,2006,16(5):611-617
[116]李永祯，申绪涧，汪连栋，等.基于辅天线的有源假目标欺骗干扰的极化识别[J].信号处理,2008,24(1):24-27
[117]李永祯，王雪松，李金梁，等.弹道导弹目标的瞬态极化识别[J].应用科学学报,2005,23(6):586-590
[118]李永祯，王雪松，王涛，等.有源诱饵的极化鉴别研究[J].国防科技大学学报,2004,26(3):83-88
[119]李永祯，王雪松，肖顺平，等.基于IPPV的真假目标极化鉴别算法[J].现代雷达,2004,26(9):38-42
[120] H. Dai, X. Wang, Y. Li. Novel discrimination method of digital deceptive jamming in mono-pulseradar[J]. Journal of Systems Engineering and Electronics,2011,22(6):910-916
[121]常宇亮，李永祯，戴幻尧，等.全极化复杂调制假目标的鉴别方法[J].电波科学学报,2010(4):651-657
[122]刘勇，李永祯，王雪松，等.基于极化分集接收的HRRP欺骗干扰鉴别[J].系统工程与电子技术,2011,33(6):1247-1252
[123]赵艳丽，王雪松，周颖，等.基于弹道平面性的有源假目标鉴别算法[J].系统仿真学报,2009,21(3):684-687
[124]赵艳丽，王雪松，饶彬，等.利用雷达滤波进行空间有源假目标识别的原理和方法[J].自然科学进展,2008,18(4):456-465
[125]赵艳丽，王雪松，王国玉，等.多假目标欺骗干扰下组网雷达跟踪技术[J].电子学报,2007,35(3):454-458
[126]赵艳丽，周颖，王雪松，等.基于动力学模型的有源假目标鉴别方法[J].国防科技大学学报,2007,29(5):60-65
[127]赵艳丽.弹道导弹雷达跟踪与识别研究[D].国防科学技术大学,2007
[128]饶彬.对抗条件下弹道目标的雷达跟踪技术研究[D].长沙:国防科学技术大学,2011
[129]饶彬，赵志超，肖顺平，等.利用最优定轨算法鉴别弹道有源假目标[J].系统工程与电子技术,2010,32(6):1195-1200
[130]饶彬，王雪松，丹梅，等.基于动力学守恒定律的弹道有源假目标鉴别方法[J].宇航学报,2009,30(3):908-913
[131] B. Rao, S. Xiao, X. Wang, et al. Maximum likelihood approach to the estimation and discriminationof exoatmospheric active phantom tracks using motion features[J]. Aerospace and ElectronicSystems, IEEE Transactions on,2012,48(1):794-819
[132] B. Rao, S. Xiao, X. Wang. Joint tracking and discrimination of exoatmospheric active decoys usingnine-dimensional parameter-augmented EKF[J]. Signal Processing,2011,91(10):2247-2258
[133] B. Rao, Y. L. Zhao, S. P. Xiao, et al. Discrimination of exo-atmospheric active decoys usingacceleration information[J]. Radar, Sonar&Navigation, IET,2010,4(4):626-638
[134]高红卫，谢良贵，文树梁，等.基于微多普勒特征的真假目标雷达识别研究[J].电波科学学报,2008,23(4):775-780
[135] H. Gao, L. Xie, S. Wen, et al. Micro-doppler signature extraction from ballistic target withmicro-motions[J]. Aerospace and Electronic Systems, IEEE Transactions on,2010,46(4):1969-1982
[136] K. Y. Guo, X. Q. Sheng. Precise recognition of warhead and decoy based on components ofmicro-doppler frequency curves[J]. SCIENCE CHINA Information Sciences,2012,55(4):850-856
[137] K. Y. Guo, X. Q. Sheng. A precise recognition approach of ballistic missile warhead and decoy[J].Journal of Electromagnetic Waves and Applications,23,2009,14(15):1867-1875
[138]郭琨毅，张永丽，盛新庆，等.基于欠定盲分离的多目标微多普勒特征提取[J].电波科学学报,2012,27(04):691-695
[139] L. H. Liu, D. Mclernon, M. Ghogho, et al. Ballistic missile detection via micro-doppler frequencyestimation from radar return[J]. DIGITAL SIGNAL PROCESSING,2012,22(1):87-95
[140] L. Liu, X. Du, M. Ghogho, et al. Precession missile feature extraction using sparse componentanalysis of radar measurements[J]. EURASIP Journal on Advances in Signal Processing,2012,2012(1):24-33
[141]周文辉，李琳，陈国海.一种有效的RGPO干扰鉴别算法及性能分析[J].电子学报,2007,35(6):1165-1169
[142]宋志勇，肖怀铁.基于回波幅度特征的拖曳式诱饵存在性检测[J].电子与信息学报,2011,33(6):1515-1519
[143]宋志勇，肖怀铁，付强，等.一种波束内目标与诱饵DOA联合估计新方法[J].国防科技大学学报,2012,34(5):96-101
[144]宋志勇，肖怀铁，祝依龙，等.基于扩展单脉冲比的拖曳式诱饵存在性检测[J].航空学报,2011,32(9):1656-1668
[145]宋志勇，肖怀铁，祝依龙，等.基于改进MCMC的波束内目标与诱饵联合参数估计[J].宇航学报,2012(4):451-459
[146] Z. Song, H. Xiao, Y. Zhu, et al. A novel approach to detect the unresolved towed decoy in terminalguidance[J]. Chinese Journal of Electronics,2012,21(2):367-373
[147] D. S. Alhumaidi. DRFM: The heart of modern digital electronic warfare systems[C].2004,18-21
[148]周峰.面向EMC的DDS信号及DDS调频信号频谱创新研究[D].北京:北京邮电大学,2008
[149] A. C. Polak, S. Dolatshahi, D. L. Goeckel. Identifying wireless users via transmitterimperfections[J]. Selected Areas in Communications, IEEE Journal on,2011,29(7):1469-1479
[150]王玉军，朱丽莉，蒋磊. LFM雷达移频干扰特征的消隐方法研究[J].雷达学报,2012,1(4):420-425
[151] E. Swiercz. Automatic classification of LFM signals for radar emitter recognition using waveletdecomposition and LVQ classifier[J]. Acta Phys. Polonica A,2011,119(4):488-494
[152] N. E. Huang, Z. Shen, S. R. Long, et al. The empirical mode decomposition and the Hilbertspectrum for nonlinear and non-stationary time series analysis[J]. Proceedings of the Royal Societyof London. Series A: Mathematical, Physical and Engineering Sciences,1998,454(1971):903-995
[153] Z. Guo, S. Li. One-dimensional frequency-domain features for aircraft recognition from radar rangeprofiles[J]. Aerospace and Electronic Systems, IEEE Transactions on,2010,46(4):1880-1892
[154] D. D. Lee, H. S. Seung. Learning the parts of objects by non-negative matrix factorization[J].Nature,1999,401:788-791
[155]范伟，唐斌.基于神经网络的欺骗式干扰类型识别[J].雷达与对抗,2007(2):43-45
[156] J. Zhang, X. Zhu, K. Wang. A waveform diversity technique for countering RGPO[C]. RadarConference,2009IET International, Guillin, China, IET,2009,1-4
[157] X. Shuai, L. Kong, J. Yang. Performance analysis of GLRT-based adaptive detector for distributedtargets in compound-Gaussian clutter[J]. SIGNAL PROCESSING,2010,90(1):16-23
[158] A. De Maio. Rao test for adaptive detection in gaussian interference with unknown covariancematrix[J]. Signal Processing, IEEE Transactions on,2007,55(7):3577-3584
[159] E. Conte, A. De Maio. Distributed target detection in compound-Gaussian noise with Rao and Waldtests[J]. Aerospace and Electronic Systems, IEEE Transactions on,2003,39(2):568-582
[160] Y. Norouzi, F. Gini, M. M. Nayebi, et al. Non-coherent radar CFAR detection based ongoodness-of-fit tests[J]. Radar, Sonar&Navigation, IET,2007,1(2):98-105
[161] T. W. Anderson, D. A. Darling. A test of goodness of fit[J]. Journal of the American StatisticalAssociation,1954:765-769
[162] O. Masqat. Anderson Darling and modified Anderson Darling tests for generalized Paretodistribution[J]. Pakistan Journal of Applied Sciences,2003,3(2):85-88
[163] X. Zhang, P. Willett, Y. Bar-Shalom. Detection and localization of multiple unresolved extendedtargets via monopulse radar signal processing[J]. Aerospace and Electronic Systems, IEEETransactions on,2009,45(2):455-472
[164] Y. Boers, H. Driessen. A particle-filter-based detection scheme[J]. Signal Processing Letters, IEEE,2003,10(10):300-302
[165] M. F. Sabahi, M. M. Hashemi, A. Sheikhi. Particle detection and it's radar application[C]. Radar,2006. CIE '06. International Conference on, Shanghai,2006,1-4
[166] G. T. Capraro, C. T. Capraro, M. C. Wicks, et al. Artificial intelligence and waveform diversity[C].Integration of Knowledge Intensive Multi-Agent Systems,2003. International Conference on,2003,270-274
[167] S. Haykin. Cognitive radar[J]. IEEE Signal Processing Magazine,2006,23(1):30-40
[168]董臻，李伟，梁甸农.基于发射信号随机初相结合调频率极性捷变的SAR抗干扰方法[J].信号处理,2008,24(3):487-490
[169]李伟，梁甸农，董臻.一种捷变调频斜率极性和限幅相结合的SAR抗干扰方法[J].遥感学报,2007,11(2):171-176
[170]朱玉鹏，张月辉，王宏强，等.基于调频率微调的ISAR抗干扰技术研究[J].信号处理,2010,26(3):417-423
[171]胡英辉，郑远，邓云凯.超混沌调相信号抗干扰技术研究[J].电子与信息学报,2008,30(07):1756-1759
[172]胡英辉，耿旭朴，邓云凯.超混沌正交多相码信号的设计与优选[J].兵工学报,2009,30(12):1632-1637
[173] P. O'Shea. A fast algorithm for estimating the parameters of a quadratic FM signal[J]. SignalProcessing, IEEE Transactions on,2004,52(2):385-393
[174] G. Liu, H. Gu, W. Su. Development of random signal radars[J]. Aerospace and Electronic Systems,IEEE Transactions on,1999,35(3):770-777
[175] H. Deng. Polyphase code design for orthogonal netted radar systems[J]. Signal Processing, IEEETransactions on,2004,52(11):3126-3135
[176] M. Dawood, R. M. Narayanan. Receiver operating characteristics for the coherent UWB randomnoise radar[J]. Aerospace and Electronic Systems, IEEE Transactions on,2001,37(2):586-594
[177] F. Alonge, M. Branciforte, F. Motta. A novel method of distance measurement based on pulseposition modulation and synchronization of chaotic signals using ultrasonic radar systems[J].Instrumentation and Measurement, IEEE Transactions on,2009,58(2):318-329
[178]韩俊，何明浩，朱元清，等.基于双谱二维特征相像系数的雷达信号分选[J].电波科学学报,2009,24(5):848-853
[179]王海华，沈晓峰.一种新的雷达辐射源信号脉内特征提取方法[J].系统工程与电子技术,2009,31(04):809-811
[180] L. Ding. Digital predistortion of power amplifiers for wireless applications[D]. Atlanta Botanical:Georgia Institute of Technology,2004
[181] S. G. Mallat, Z. Zhang. Matching pursuits with time-frequency dictionaries[J]. Signal Processing,IEEE Transactions on,1993,41(12):3397-3415
[182] A. Bultan. A four-parameter atomic decomposition of chirplet[J]. Signal Processing, IEEETransactions on,1999,47(3):731-745
[183] X. Wang, J. Liu, H. Meng, et al. Novel atomic decomposition algorithm for parameter estimation ofmultiple superimposed gaussian chirplet[J]. Radar, Sonar&Navigation, IET,2011,5(8):854-861
[2]赵国庆.雷达对抗原理[M].西安:西安电子科技大学出版社,1999
[3] A. J. Elbirt. Information warfare: are you at risk?[J]. Technology and Society Magazine, IEEE,2003,22(4):13-19
[4] S. L. Johnston. Radar electronic counter-countermeasures[J]. Aerospace and Electronic Systems,IEEE Transactions on,1978,14(1):109-117
[5] R. Schroer. Electronic warfare.[A century of powered flight:1903-2003][J]. Aerospace and ElectronicSystems Magazine, IEEE,2003,18(7):49-54
[6] N. Li, Y. Zhang. A survey of radar ECM and ECCM[J]. Aerospace and Electronic Systems, IEEETransactions on,1995,31(3):1110-1120
[7] J. Guo, J. Li, Q. Lv. Survey on radar ECCM methods and trends in its developments[C]. Radar,2006.CIE '06. International Conference on, Shanghai,2006,1-4
[8]施龙飞.雷达极化抗干扰技术研究[D].长沙:国防科学技术大学,2007
[9] G. W. Stimson. Introduction to airborne radar[M]. New Jersey, USA: SciTech Pub.,1998
[10] S. A. Vakin, L. N. Shustov, R. H. Dunwell. Fundamentals of electronic warfare[M]. Boston: ArtechHouse,2001
[11] R. M. Davis, R. L. Fante, T. P. Guella, et al. Interference suppression via operating frequencyselection[J]. Antennas and Propagation, IEEE Transactions on,1999,47(4):637-645
[12] M. Soumekh. SAR-ECCM using phase-perturbed LFM chirp signals and DRFM repeat jammerpenalization[J]. Aerospace and Electronic Systems, IEEE Transactions on,2006,42(1):191-205
[13] J. Akhtar. An ECCM scheme for orthogonal independent range-focusing of real and false targets[C].Radar Conference,2007IEEE, Boston, MA,2007,846-849
[14] J. Akhtar. Orthogonal block coded ECCM schemes against repeat radar jammers[J]. Aerospace andElectronic Systems, IEEE Transactions on,2009,45(3):1218-1226
[15] J. Akhtar. Removal of range ambiguities with orthogonal block coding techniques[J]. Circuits,Systems, and Signal Processing,2010,29(2):311-330
[16] J. Schuerger, D. Garmatyuk. Performance of random OFDM radar signals in deception jammingscenarios[C]. Radar Conference,2009IEEE, Pasadena, CA, IEEE,2009,1-6
[17] F. Kural, Y. Ozkazanc. A method for detecting RGPO/VGPO jamming[C]. Signal Processing andCommunications Applications Conference,2004,237-240
[18] H. H. M. Ghouz, F. I. A. Elghany, M. M. Qutb. Adaptive space-time processing for interferencesuppression in phased array radar systems. I. Search radar[C]. Radio Science Conference,2000.17th NRSC '2000. Seventeenth National, Minufiya,2000,1-8
[19] H. H. M. Ghouz, F. I. A. Elghany, M. M. Qutb. Adaptive space-time processing for interferencesuppression in phased array radar systems. II. Tracking radar[C]. Radio Science Conference,2000.17th NRSC '2000. Seventeenth National, Minufiya,2000,91-97
[20] Y. Kai-Bor, D. J. Murrow. Adaptive digital beamforming for angle estimation in jamming[J].Aerospace and Electronic Systems, IEEE Transactions on,2001,37(2):508-523
[21] W. R. Blanding, W. Koch, U. Nickel. Adaptive phased-array tracking in ECM using negativeinformation[J]. Aerospace and Electronic Systems, IEEE Transactions on,2009,45(1):152-166
[22] D. S. Garmatyuk, R. M. Narayanan. ECCM capabilities of an ultrawideband bandlimited randomnoise imaging radar[J]. Aerospace and Electronic Systems, IEEE Transactions on,2002,38(4):1243-1255
[23] L. Rosenberg, D. Gray. Anti-jamming techniques for multichannel SAR imaging[J]. Radar, Sonarand Navigation, IEE Proceedings-,2006,153(3):234-242
[24] P. Stavroulakis, N. Farsaris, T. D. Xenos. Anti-jamming transmitter independent radar networks[C].Signal Processing, Communications and Networking,2008. ICSCN '08. International Conferenceon, Chennai,2008,269-273
[25]贲德.机载脉冲多普勒(PD)雷达的工作特点及抗干扰措施[J].现代雷达,2000,22(4):1-6
[26]张光义.提高雷达系统抗干扰能力的一些措施[J].现代雷达,2001,23(1):6-12
[27]常宇亮.瞬态极化雷达测量、检测与抗干技术研究[D].长沙:国防科学技术大学,2010
[28]刘勇.动态目标极化特性测量与极化雷达抗干扰新方法研究[D].长沙:国防科学技术大学,2011
[29]周万幸.一种新型极化抗干扰技术研究[J].电子学报,2009,37(3):454-458
[30]宋立众，乔晓林，吴群.一种弹载相控阵雷达及其极化滤波方法[J].电波科学学报,2009,24(06):1071-1077
[31]宋立众，乔晓林，吴群.一种基于极化DBF的制导雷达抗干扰方法[J].电波科学学报,2010,25(01):109-116
[32]宋立众，乔晓林，吴群.一种极化分集制导雷达及低截获概率信号设计[J].系统工程与电子技术,2009,31(12):2853-2858
[33]张新相，吴铁平，陈天麒.随机信号雷达抗干扰性能分析[J].电波科学学报,2008,23(01):189-194
[34]冯祥芝，许小剑.随机线性调频斜率SAR抗欺骗干扰方法研究[J].系统工程与电子技术,2009,31(01):69-73
[35]冯祥芝，许小剑.混沌码正交频分复用SAR抗干扰能力研究[J].系统仿真学报,2009,21(22):7359-7362
[36]张劲东.自适应雷达系统中波形分集技术的研究[D].南京:南京理工大学,2010
[37]张劲东，李彧晟，朱晓华.基于波形分集的雷达抗欺骗干扰[J].数据采集与处理,2010,25(02):138-142
[38] J. Zhang, D. Zhu, G. Zhang. New antivelocity deception jamming technique using pulses withadaptive initial phases[J]. Aerospace and Electronic Systems, IEEE Transactions on,2013,49(2):1290-1300
[39]郑远，胡英辉，邓云凯.混沌调频雷达成像与欺骗干扰分析[J].系统工程与电子技术,2009,31(05):1071-1074
[40]郑远，胡英辉，邓云凯.混沌相位编码信号成像与反欺骗干扰仿真[J].系统仿真学报,2008,20(15):3962-3965
[41] Y. Deng, Y. Hu, X. Geng. Hyper chaotic logistic phase coded signal and its sidelobe suppression[J].Aerospace and Electronic Systems, IEEE Transactions on,2010,46(2):672-686
[42]谢春健，郭陈江，许家栋.调频率正负交替变化的SAR成像及抗欺骗干扰方法[J].计算机应用,2010,30(05):1383-1389
[43]谢春健，郭陈江，许家栋.基于混沌信号的SAR抗距离向相干干扰方法[J].计算机仿真,2010,27(11):132-135
[44]谢春健，李建周，郭陈江，等.基于Logistic混沌映射移频的SAR转发干扰方法[J].系统工程与电子技术,2011,33(10):2210-2216
[45] G. Lu, B. Tang, G. Gui. Deception ECM signals cancellation processor with joint time-frequencypulse diversity[J]. IEICE Electronics Express,2011,8(19):1608-1613
[46]卢刚.雷达有源假目标抑制方法研究[D].成都:电子科技大学,2012
[47] G. Lu, B. Tang. Deception jammer rejection using pulse diversity in joint slow/fast-time domain[J].Journal of the Chinese Institute of Engineers,2013,36(3):405-410
[48] G. Lu, S. Liao, S. Luo, et al. Cancellation of complicated DRFM range false targets via temporalpulse diversity[J]. Progress In Electromagnetics Research,2010,16:69-84
[49]张淑宁，赵惠昌.伪码引信抗欺骗干扰的互相关正交投影联合法[J].南京理工大学学报(自然科学版),2007,31(04):509-513
[50]张淑宁，赵惠昌，熊刚.基于延时变化量估计的伪码引信抗欺骗式干扰方法[J].宇航学报,2008,29(1):326-330
[51]杨莘元，程万翔，姜弢，等.自适应零点形成技术抑制雷达相干干扰[J].哈尔滨工程大学学报,1999,20(4):69-73
[52]白渭雄，张文，苗淼.旁瓣干扰对抗技术研究[J].系统工程与电子技术,2009,31(1):86-90
[53]张子敬，张浩.校正谱分析在导引头抗干扰中的应用[J].西安电子科技大学学报,1997(S1):96-102
[54]张子敬，张浩，吴洹.抗速度门拖引的解线性调频方法[J].西安电子科技大学学报,1996,23(02):211-217
[55]陈浩，何明浩，毛五星.小波分解在雷达抗速度欺骗干扰中的运用[J].空军雷达学院学报,2006,20(1):31-33
[56] M. H. Sun, B. Tang. Suppression of smeared spectrum ECM signal[J]. Journal of the ChineseInstitute of Engineers,2009,32(3):407-413
[57]孙闽红.雷达抗有源欺骗式干扰算法研究[D].成都:电子科技大学,2008
[58]罗双才，唐斌.一种基于盲分离的欺骗干扰抑制算法[J].电子与信息学报,2011,33(12):2801-2806
[59]罗双才，唐斌.一种空域-极化域联合的雷达欺骗干扰抑制算法[J].信号处理,2012,28(3):443-448
[60]卢刚，唐斌，罗双才. LFM雷达中DRFM假目标自适应对消方法[J].系统工程与电子技术,2011,33(08):1760-1764
[61] G. Lu, D. Zeng, B. Tang. Anti-jamming filtering for DRFM repeat jammer based on stretchprocessing[C]. Signal Processing Systems (ICSPS),20102nd International Conference on,2010,78-82
[62] G. Lu, S. Luo, H. Gu, et al. Adaptive biased weight-based RGPO/RGPI ECCM algorithm[C]. Radar(Radar),2011IEEE CIE International Conference on, Chengdu, IEEE,2011,1067-1070
[63]朱良，曹鹏，禹卫东.基于移频干扰的成像算法抗干扰性能分析[J].电子学报,2011(S1):47-51
[64]李江源，王建国.利用复杂调制LFM信号的SAR抗欺骗干扰技术[J].电子与信息学报,2008,30(9):2111-2114
[65]李云涛，陈永光，贾鑫，等.多载频MIMO-SAR对消处理抗欺骗干扰[J].电子学报,2012,40(9):1790-1794
[66]唐波，王卫延.干涉合成孔径雷达抗干扰性能分析[J].电子与信息学报,2006,28(10):1809-1811
[67]李侠，蔡万勇，花良发，等.责任区雷达组网系统抗干扰优化部署算法[J].系统工程与电子技术,2007,29(8):1254-1257
[68]徐海全，王国宏，关成斌.远距离支援干扰下的目标跟踪技术[J].北京航空航天大学学报,2011,37(11):1353-1358
[69]徐海全，王国宏，关成斌.分布式干扰下雷达网的目标跟踪技术[J].兵工学报,2011,32(6):764-769
[70]刘兆磊，王国宏，张光义，等.机载火控雷达距离拖引目标的交互式多模型跟踪方法[J].航空学报,2005,26(4):465-469
[71]李世忠，王国宏，吴巍，等.分布式干扰下组网雷达目标检测与跟踪技术[J].系统工程与电子技术,2012,34(4):782-788
[72] M. Ahmed. Parameterized DRFM modulator for ECM Systems[J]. International Journal ofAdvanced Electronics and Communication Systems,2012,1(1):56-60
[73] C. M. Kwak. Application of DRFM in ECM for pulse type radar[C]. Infrared, Millimeter, andTerahertz Waves,2009. IRMMW-THz2009.34th International Conference on, Busan,2009,1-2
[74] K. Olivier, J. E. Cilliers, M. du Plessis. Design and performance of wideband DRFM for radar testand evaluation[J]. Electronics letters,2011,47(14):824-825
[75] C. J. Hill, V. Truffert. Statistical processing techniques for detecting DRFM repeat-jam radarsignals[C]. Signal Processing Techniques for Electronic Warfare, IEE Colloquium on, London,1992,1-6
[76] W. D. Blair, M. Brandt-Pearce. Discrimination of target and RGPO echoes using frequencydiversity[C]. System Theory,1997., Proceedings of the Twenty-Ninth Southeastern Symposium on,Cookeville, TN,1997,509-513
[77] P. R. Kalata, T. A. Chmielewski. Range gate pull off (RGPO): detection, observability and α-βtarget tracking[C]. System Theory,1997, Proceedings of the Twenty-Ninth SoutheasternSymposium on, Cookeville, TN,1997,505-508
[78] W. D. Blair, G. A. Watson, T. Kirubarajan, et al. Benchmark for radar allocation and tracking inECM[J]. Aerospace and Electronic Systems, IEEE Transactions on,1998,34(4):1097-1114
[79] T. Kirubarajan, Y. Bar-Shalom, W. D. Blair, et al. IMMPDAF for radar management and trackingbenchmark with ECM[J]. Aerospace and Electronic Systems, IEEE Transactions on,1998,34(4):1115-1134
[80] X. R. Li, B. Slocumband, W. Phillip. Tracking in the presence of range deception ECM and clutterby decomposition and fusion[C]. SPIE Conference on Signal and Data Processing of Small Targets,Denver, Colorado, USA, Society of Photo-Optical Instrumentation Engineers,1999,198-210
[81] V. Behar, C. Kabakchiev, X. R. Li. Excision techniques for reduction of the flow of the RGPO whensolving the benchmark problem[C]. Radar Conference,2000. The Record of the IEEE2000International, Alexandria, VA,2000,862-866
[82] S. D. Berger. Digital radio frequency memory linear range gate stealer spectrum[J]. Aerospace andElectronic Systems, IEEE Transactions on,2003,39(2):725-735
[83] S. D. Berger. The spectrum of a digital radio frequency memory linear range gate stealer electronicattack signal[C]. Radar Conference,2001. Proceedings of the2001IEEE, Atlanta, GA,2001,27-30
[84] M. Greco, F. Gini, A. Farina. Combined effect of phase and RGPO delay quantization on jammingsignal spectrum[C]. Radar Conference,2005IEEE International,2005,37-42
[85] M. Greco, F. Gini, A. Farina, et al. Effect of phase and range gate pull-off delay quantisation onjammer signal[J]. Radar, Sonar and Navigation, IEE Proceedings-,2006,153(5):454-459
[86] M. Greco, F. Gini, A. Farina. Radar detection and classification of jamming signals belonging to acone class[J]. Signal Processing, IEEE Transactions on,2008,56(5):1984-1993
[87] F. Bandiera, A. Farina, D. Orlando, et al. Detection algorithms to discriminate between radar targetsand ECM signals[J]. Signal Processing, IEEE Transactions on,2010,58(12):5984-5993
[88] B. Tao. An ECCM model and the technical development trends to the demands of the future EWcombat[J]. Aerospace and Electronic Systems Magazine, IEEE,1994,9(6):12-16
[89]保铮，谢维信，朱宾.雷达系统抗欺骗型干扰性能的测度[J].电子学报,1989,17(06):13-20
[90]贾鑫，郭桂蓉，梁泰基.一种雷达干扰信号识别的映射统计方法及其实验研究[J].指挥技术学院学报,1994,5(02):14-17
[91]贾鑫，梁泰基，郭桂蓉.一种基于雷达视频波形的噪声调频干扰带宽辨识算法的研究[J].电子学报,1991,19(04):116-119
[92]赵雪飞，赵川，刘峥. PD雷达抗距离-速度同步拖引干扰的频谱识别法[J].雷达与对抗,2005(03):21-24
[93]吕强，李建勋，秦江敏，等.基于神经网络的雷达抗转发式距离欺骗干扰方法[J].系统工程与电子技术,2005,27(2):240-243
[94]李建勋，秦江敏，马晓岩.雷达抗应答式欺骗干扰中的特征提取研究[J].空军雷达学院学报,2004,18(2):4-7
[95]李建勋，秦江敏，马晓岩.基于神经网络的雷达抗应答式欺骗干扰方法[J].空军雷达学院学报,2003,17(4):19-21
[96]李建勋，唐斌，吕强.双谱特征提取在欺骗式干扰方式识别中的应用[J].电子科技大学学报,2009,38(3):329-332
[97]户锋刚，阮怀林，曾昭勇.对距离-速度欺骗干扰的识别方法[J].电子信息对抗技术,2007,22(3):36-39
[98]张红昌，阮怀林.基于支持向量机的雷达欺骗性干扰类型识别[J].火控雷达技术,2009,38(3):17-21
[99]陈建春，耿富录.基于线性预测滤波的抗速度欺骗干扰技术[J].系统工程与电子技术,2002,24(2):22-24
[100]陈建春.速度拖引干扰的频谱识别技术[J].火控雷达技术,1998,27(3):37-42
[101]张翼飞，胡林华，董云龙.一种有效识别速度欺骗干扰的方法[J].空军雷达学院学报,2009,23(3):181-183
[102]张善文，赵栓堂，等.速度拖引干扰下运动目标检测[J].系统工程与电子技术,2001,23(5):57-59
[103]常成.雷达欺骗式干扰检测与实现[D].上海:上海交通大学,2009
[104]熊伟，曹兰英，郝志梅.基于多尺度相像系数的雷达干扰类型频域识别[J].计算机仿真,2010,27(3):19-22
[105]孙闽红，唐斌.距离-速度同步拖引欺骗干扰的频谱特征分析[J].系统工程与电子技术,2009,31(1):83-85
[106]孙闽红，唐斌.基于原子分解理论的雷达欺骗式干扰信号特征提取[J].电波科学学报,2008,23(3):550-554
[107]范伟.雷达有源干扰信号特征分析与识别算法研究[D].成都:电子科技大学,2007
[108]刘旻.雷达复合干扰信号特征提取及智能识别算法研究[D].电子科技大学,2008
[109]熊英，刘旻，唐斌，等.基于盒维数与LZ复杂度的雷达复合干扰特征提取方法[J].数据采集与处理,2008,23(6):663-667
[110]顾海燕.距离-速度有源雷达干扰建模与对抗方法研究[D].成都:电子科技大学,2011
[111]李永平，卢刚，田晓，等.基于模糊函数的SMSP和C＆I干扰识别算法[J].航空兵器,2011(4):51-54
[112] Y. Li, Y. Xiong, B. Tang. SMSP jamming identification based on matched signal transform[C].Computational Problem-Solving (ICCP),2011International Conference on, Chengdu, IEEE,2011,182-185
[113]王涛.弹道中段目标极化域特征提取与识别[D].长沙:国防科学技术大学,2006
[114]王涛，王雪松，刘进，等.干扰背景下瞬时极化测量雷达的目标识别预处理技术[J].电子与信息学报,2008,30(10):2333-2337
[115]王涛，王雪松，肖顺平.随机调制单极化有源假目标的极化鉴别研究[J].自然科学进展,2006,16(5):611-617
[116]李永祯，申绪涧，汪连栋，等.基于辅天线的有源假目标欺骗干扰的极化识别[J].信号处理,2008,24(1):24-27
[117]李永祯，王雪松，李金梁，等.弹道导弹目标的瞬态极化识别[J].应用科学学报,2005,23(6):586-590
[118]李永祯，王雪松，王涛，等.有源诱饵的极化鉴别研究[J].国防科技大学学报,2004,26(3):83-88
[119]李永祯，王雪松，肖顺平，等.基于IPPV的真假目标极化鉴别算法[J].现代雷达,2004,26(9):38-42
[120] H. Dai, X. Wang, Y. Li. Novel discrimination method of digital deceptive jamming in mono-pulseradar[J]. Journal of Systems Engineering and Electronics,2011,22(6):910-916
[121]常宇亮，李永祯，戴幻尧，等.全极化复杂调制假目标的鉴别方法[J].电波科学学报,2010(4):651-657
[122]刘勇，李永祯，王雪松，等.基于极化分集接收的HRRP欺骗干扰鉴别[J].系统工程与电子技术,2011,33(6):1247-1252
[123]赵艳丽，王雪松，周颖，等.基于弹道平面性的有源假目标鉴别算法[J].系统仿真学报,2009,21(3):684-687
[124]赵艳丽，王雪松，饶彬，等.利用雷达滤波进行空间有源假目标识别的原理和方法[J].自然科学进展,2008,18(4):456-465
[125]赵艳丽，王雪松，王国玉，等.多假目标欺骗干扰下组网雷达跟踪技术[J].电子学报,2007,35(3):454-458
[126]赵艳丽，周颖，王雪松，等.基于动力学模型的有源假目标鉴别方法[J].国防科技大学学报,2007,29(5):60-65
[127]赵艳丽.弹道导弹雷达跟踪与识别研究[D].国防科学技术大学,2007
[128]饶彬.对抗条件下弹道目标的雷达跟踪技术研究[D].长沙:国防科学技术大学,2011
[129]饶彬，赵志超，肖顺平，等.利用最优定轨算法鉴别弹道有源假目标[J].系统工程与电子技术,2010,32(6):1195-1200
[130]饶彬，王雪松，丹梅，等.基于动力学守恒定律的弹道有源假目标鉴别方法[J].宇航学报,2009,30(3):908-913
[131] B. Rao, S. Xiao, X. Wang, et al. Maximum likelihood approach to the estimation and discriminationof exoatmospheric active phantom tracks using motion features[J]. Aerospace and ElectronicSystems, IEEE Transactions on,2012,48(1):794-819
[132] B. Rao, S. Xiao, X. Wang. Joint tracking and discrimination of exoatmospheric active decoys usingnine-dimensional parameter-augmented EKF[J]. Signal Processing,2011,91(10):2247-2258
[133] B. Rao, Y. L. Zhao, S. P. Xiao, et al. Discrimination of exo-atmospheric active decoys usingacceleration information[J]. Radar, Sonar&Navigation, IET,2010,4(4):626-638
[134]高红卫，谢良贵，文树梁，等.基于微多普勒特征的真假目标雷达识别研究[J].电波科学学报,2008,23(4):775-780
[135] H. Gao, L. Xie, S. Wen, et al. Micro-doppler signature extraction from ballistic target withmicro-motions[J]. Aerospace and Electronic Systems, IEEE Transactions on,2010,46(4):1969-1982
[136] K. Y. Guo, X. Q. Sheng. Precise recognition of warhead and decoy based on components ofmicro-doppler frequency curves[J]. SCIENCE CHINA Information Sciences,2012,55(4):850-856
[137] K. Y. Guo, X. Q. Sheng. A precise recognition approach of ballistic missile warhead and decoy[J].Journal of Electromagnetic Waves and Applications,23,2009,14(15):1867-1875
[138]郭琨毅，张永丽，盛新庆，等.基于欠定盲分离的多目标微多普勒特征提取[J].电波科学学报,2012,27(04):691-695
[139] L. H. Liu, D. Mclernon, M. Ghogho, et al. Ballistic missile detection via micro-doppler frequencyestimation from radar return[J]. DIGITAL SIGNAL PROCESSING,2012,22(1):87-95
[140] L. Liu, X. Du, M. Ghogho, et al. Precession missile feature extraction using sparse componentanalysis of radar measurements[J]. EURASIP Journal on Advances in Signal Processing,2012,2012(1):24-33
[141]周文辉，李琳，陈国海.一种有效的RGPO干扰鉴别算法及性能分析[J].电子学报,2007,35(6):1165-1169
[142]宋志勇，肖怀铁.基于回波幅度特征的拖曳式诱饵存在性检测[J].电子与信息学报,2011,33(6):1515-1519
[143]宋志勇，肖怀铁，付强，等.一种波束内目标与诱饵DOA联合估计新方法[J].国防科技大学学报,2012,34(5):96-101
[144]宋志勇，肖怀铁，祝依龙，等.基于扩展单脉冲比的拖曳式诱饵存在性检测[J].航空学报,2011,32(9):1656-1668
[145]宋志勇，肖怀铁，祝依龙，等.基于改进MCMC的波束内目标与诱饵联合参数估计[J].宇航学报,2012(4):451-459
[146] Z. Song, H. Xiao, Y. Zhu, et al. A novel approach to detect the unresolved towed decoy in terminalguidance[J]. Chinese Journal of Electronics,2012,21(2):367-373
[147] D. S. Alhumaidi. DRFM: The heart of modern digital electronic warfare systems[C].2004,18-21
[148]周峰.面向EMC的DDS信号及DDS调频信号频谱创新研究[D].北京:北京邮电大学,2008
[149] A. C. Polak, S. Dolatshahi, D. L. Goeckel. Identifying wireless users via transmitterimperfections[J]. Selected Areas in Communications, IEEE Journal on,2011,29(7):1469-1479
[150]王玉军，朱丽莉，蒋磊. LFM雷达移频干扰特征的消隐方法研究[J].雷达学报,2012,1(4):420-425
[151] E. Swiercz. Automatic classification of LFM signals for radar emitter recognition using waveletdecomposition and LVQ classifier[J]. Acta Phys. Polonica A,2011,119(4):488-494
[152] N. E. Huang, Z. Shen, S. R. Long, et al. The empirical mode decomposition and the Hilbertspectrum for nonlinear and non-stationary time series analysis[J]. Proceedings of the Royal Societyof London. Series A: Mathematical, Physical and Engineering Sciences,1998,454(1971):903-995
[153] Z. Guo, S. Li. One-dimensional frequency-domain features for aircraft recognition from radar rangeprofiles[J]. Aerospace and Electronic Systems, IEEE Transactions on,2010,46(4):1880-1892
[154] D. D. Lee, H. S. Seung. Learning the parts of objects by non-negative matrix factorization[J].Nature,1999,401:788-791
[155]范伟，唐斌.基于神经网络的欺骗式干扰类型识别[J].雷达与对抗,2007(2):43-45
[156] J. Zhang, X. Zhu, K. Wang. A waveform diversity technique for countering RGPO[C]. RadarConference,2009IET International, Guillin, China, IET,2009,1-4
[157] X. Shuai, L. Kong, J. Yang. Performance analysis of GLRT-based adaptive detector for distributedtargets in compound-Gaussian clutter[J]. SIGNAL PROCESSING,2010,90(1):16-23
[158] A. De Maio. Rao test for adaptive detection in gaussian interference with unknown covariancematrix[J]. Signal Processing, IEEE Transactions on,2007,55(7):3577-3584
[159] E. Conte, A. De Maio. Distributed target detection in compound-Gaussian noise with Rao and Waldtests[J]. Aerospace and Electronic Systems, IEEE Transactions on,2003,39(2):568-582
[160] Y. Norouzi, F. Gini, M. M. Nayebi, et al. Non-coherent radar CFAR detection based ongoodness-of-fit tests[J]. Radar, Sonar&Navigation, IET,2007,1(2):98-105
[161] T. W. Anderson, D. A. Darling. A test of goodness of fit[J]. Journal of the American StatisticalAssociation,1954:765-769
[162] O. Masqat. Anderson Darling and modified Anderson Darling tests for generalized Paretodistribution[J]. Pakistan Journal of Applied Sciences,2003,3(2):85-88
[163] X. Zhang, P. Willett, Y. Bar-Shalom. Detection and localization of multiple unresolved extendedtargets via monopulse radar signal processing[J]. Aerospace and Electronic Systems, IEEETransactions on,2009,45(2):455-472
[164] Y. Boers, H. Driessen. A particle-filter-based detection scheme[J]. Signal Processing Letters, IEEE,2003,10(10):300-302
[165] M. F. Sabahi, M. M. Hashemi, A. Sheikhi. Particle detection and it's radar application[C]. Radar,2006. CIE '06. International Conference on, Shanghai,2006,1-4
[166] G. T. Capraro, C. T. Capraro, M. C. Wicks, et al. Artificial intelligence and waveform diversity[C].Integration of Knowledge Intensive Multi-Agent Systems,2003. International Conference on,2003,270-274
[167] S. Haykin. Cognitive radar[J]. IEEE Signal Processing Magazine,2006,23(1):30-40
[168]董臻，李伟，梁甸农.基于发射信号随机初相结合调频率极性捷变的SAR抗干扰方法[J].信号处理,2008,24(3):487-490
[169]李伟，梁甸农，董臻.一种捷变调频斜率极性和限幅相结合的SAR抗干扰方法[J].遥感学报,2007,11(2):171-176
[170]朱玉鹏，张月辉，王宏强，等.基于调频率微调的ISAR抗干扰技术研究[J].信号处理,2010,26(3):417-423
[171]胡英辉，郑远，邓云凯.超混沌调相信号抗干扰技术研究[J].电子与信息学报,2008,30(07):1756-1759
[172]胡英辉，耿旭朴，邓云凯.超混沌正交多相码信号的设计与优选[J].兵工学报,2009,30(12):1632-1637
[173] P. O'Shea. A fast algorithm for estimating the parameters of a quadratic FM signal[J]. SignalProcessing, IEEE Transactions on,2004,52(2):385-393
[174] G. Liu, H. Gu, W. Su. Development of random signal radars[J]. Aerospace and Electronic Systems,IEEE Transactions on,1999,35(3):770-777
[175] H. Deng. Polyphase code design for orthogonal netted radar systems[J]. Signal Processing, IEEETransactions on,2004,52(11):3126-3135
[176] M. Dawood, R. M. Narayanan. Receiver operating characteristics for the coherent UWB randomnoise radar[J]. Aerospace and Electronic Systems, IEEE Transactions on,2001,37(2):586-594
[177] F. Alonge, M. Branciforte, F. Motta. A novel method of distance measurement based on pulseposition modulation and synchronization of chaotic signals using ultrasonic radar systems[J].Instrumentation and Measurement, IEEE Transactions on,2009,58(2):318-329
[178]韩俊，何明浩，朱元清，等.基于双谱二维特征相像系数的雷达信号分选[J].电波科学学报,2009,24(5):848-853
[179]王海华，沈晓峰.一种新的雷达辐射源信号脉内特征提取方法[J].系统工程与电子技术,2009,31(04):809-811
[180] L. Ding. Digital predistortion of power amplifiers for wireless applications[D]. Atlanta Botanical:Georgia Institute of Technology,2004
[181] S. G. Mallat, Z. Zhang. Matching pursuits with time-frequency dictionaries[J]. Signal Processing,IEEE Transactions on,1993,41(12):3397-3415
[182] A. Bultan. A four-parameter atomic decomposition of chirplet[J]. Signal Processing, IEEETransactions on,1999,47(3):731-745
[183] X. Wang, J. Liu, H. Meng, et al. Novel atomic decomposition algorithm for parameter estimation ofmultiple superimposed gaussian chirplet[J]. Radar, Sonar&Navigation, IET,2011,5(8):854-861