基于雷达测量的导弹目标微动特征提取
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摘要
弹道中段是导弹防御系统实施目标拦截的关键阶段，也是目标识别最具挑战性的阶段。基于弹道中段的雷达特征提取是弹道导弹防御系统中目标识别的关键技术之一。本文以弹道导弹防御中的雷达目标识别为背景，基于不同形式的雷达信号对微动导弹目标的特征提取相关技术进行了研究。
第一章回顾和总结了弹道导弹目标识别技术的发展状况，并简要介绍了中段弹道导弹目标识别技术的特点及面临的挑战，以及当前对中段弹道导弹目标进行特征提取和目标识别的主要技术手段。
第二章建立了雷达观测微动导弹目标的观测模型，对微动导弹的遮挡效应以及动态目标的RCS闪烁效应进行了详细的数学推导和分析，并讨论了微动目标雷达回波信号的微多普勒调制效应，以及动态RCS序列的周期与目标微动频率的关系。本章研究内容为后续的特征提取相关技术的研究奠定了基础。
第三章研究了基于动态RCS特性的弹道导弹进动频率提取方法。首先分析了雷达测量系统对RCS特性的影响，并将目标的RCS闪烁效应处理为乘性随机过程，建立了详细的锥体导弹动态RCS观测模型。在此基础上提出了两种准最大似然估计方法提取导弹目标的进动频率，分别为乘性噪声最大似然估计和高斯最大似然估计法，推导了乘性噪声最大似然估计方法的克拉美罗界。仿真实验结果验证了考虑RCS闪烁效应的必要性，以及本章所提方法的鲁棒性和有效性。
第四章提出了一种基于雷达回波信号时频图纹理的周期性估计微多普勒调制频率的方法。该方法从现象学的角度在宏观上分析了带尾翼自旋导弹雷达回波信号时频图纹理的周期性与微多普勒调制频率的关系。借鉴图像处理中纹理分析的思路，将时频谱图看成图像，结合二维傅里叶变换和自相关算法提取其纹理的周期，进而实现了对导弹目标微动频率的估计。该方法不受雷达观测姿态角度的影响，易于工程实现，且计算量较小，适用于先验知识较少的情况下对微动频率的提取。仿真实验验证了该方法的有效性，且在低信噪比条件下仍然适用。
第五章从节约导弹防御系统时间资源和有效利用雷达测量数据的角度出发，研究了基于分段非均匀雷达观测数据提取微动导弹目标的进动频率参数和散射中心位置信息的方法。根据导弹目标在高频区的电磁散射中心具有稀疏性这一特点，构造了包含进动频率的稀疏成份分析含参字典族，并建立了雷达回波信号的稀疏表征模型。在此基础上，将非线性最小二乘拟合和正交匹配追踪算法相结合，对进动导弹的雷达回波信号进行了稀疏重构，进而提取了导弹的进动频率和散射中心相对位置信息。该方法为导弹防御系统时间资源受限条件下的目标特征提取和识别技术提供了一种解决思路。
论文最后对研究内容进行了总结并给出了进一步研究方向。
Mid-course phase is the one that is most attractive for interception of a ballistic mis-sile (BM) warhead. However decoy releasing makes this phase of the flight the mostdifficult for target discrimination. Extracting appropriate feature parameters from radarreturns is a key technique in radar target discrimination of a BM. The aim of this paperis to analyze the micro-Doppler features of ballistic missiles during flight, and investigatemethods to extract the appropriate feature parameters.
InChapterOne, thedevelopmentstatusofthetargetdiscriminationtechnologyoftheBM is reviewed firstly. And then the characteristics and challenges of the technology inthe mid-course phase are briefly introduced. The main methods of the feature extractionand target discrimination of the BM in the mid-course phase are summarized as well. Themajor contributions of this dissertation are listed at the end of this chapter.
In Chapter Two, the geometric model of the BM observing by a radar is establishedsystematically. The shield effect of the spinning BM and the dynamic RCS scintillationare deduced in detail. The micro-Doppler effect of the radar echo from a BM with micro-motion is investigated, and the relationship between the the RCS sequence period and theprecession frequency of the BM is discussed. The study in this chapter is the foundationof the following research on the feature extraction of the BM targets.
In Chapter Three, the research mainly focuses on the precession frequency estima-tion based on the BM dynamic radar cross section (RCS) sequence. Firstly the influencesof the radar measure system to the RCS distribution is derived. The scintillation effectis taken into account and modeled as a multiplicative noise. And then the dynamic RCSdistribution model of a precessing conical missile is established. Two pseudo maximumlikelihoodestimation(MLE)approachestoextracttheparameterofmissileprecessionfre-quency are proposed. The first approach ignores the additive noise (i.e., assuming the in-finite signal-to-noise ratio (SNR)). The second approach enforces a Gaussian distributionon both additive and multiplicative noise components. The Cram′er-Rao Lower Bound(CRLB) corresponding to the maximum SNR scenario is derived. Simulations indicatethat accounting for the multiplicative noise in the estimation significantly improves esti-mationperformance,andalsoshowtherobustnessandvalidationoftheproposedmethods.
In Chapter Four, a method to estimated the micro-Doppler modulation frequencythroughanalyzingtheperiodicstructureoftheresultingtime-frequencydistribution(TFD)spectrogram is presented. The relationship between the texture period of the TFD ofa spinning BM and the micro-Doppler modulation frequency is analyzed from the phe-nomenology perspective. Based on the texture analysis in the image processing theory,the resultant TFD spectrogram is treated as an image (with periodic features along thetime axis). The2-D DFT (followed by autocorrelation) is then used to exploit the wellknown periodicity of the micro-Doppler signature in the TF domain, to better estimate themicro-Doppler modulation frequency via a simple cost effective and system friendly way.The method presented in this chapter has low computational cost, and does not need anyprior information about the signals, which satisfies the special demands of a BM targetrecognition system. The simulation results also indicate that the method work well underthe conditions of low signal to noise ratio (SNR).
In Chapter Five, aiming at saving the time resources in the ballistic missile defense(BMD) system and taking full advantage of radar measurements, a feature estimationmethod through a set of non-uniformly sampled radar signal is investigated. The esti-matedfeaturesincludethetheprecessionfrequencyandthescatteringcenters'distributioninformation of a BM with micro-motion. According to the sparsity nature of the BM scat-tering centers in the high frequency region, the parametric dictionary based on the sparsecomponent analysis (SCA) theory is constructed and the radar signal sampling model isestablished. And then, the algorithms of the nonlinear least square (NLLS) and the or-thogonal matching pursuit (OMP) are jointly employed to reconstruct the radar signal.Therefore, the precession frequency and the scattering centers' location of the precess-ing BM are estimated according to the sparse representation of the signal. The methodproposes a new notion for the feature extraction of the BM target under the restriction oflimited time resource in the ballistic missile defense system.
In Chapter Six, the work of the dissertation is summarized and the related furtherresearch is discussed.
第一章回顾和总结了弹道导弹目标识别技术的发展状况，并简要介绍了中段弹道导弹目标识别技术的特点及面临的挑战，以及当前对中段弹道导弹目标进行特征提取和目标识别的主要技术手段。
第二章建立了雷达观测微动导弹目标的观测模型，对微动导弹的遮挡效应以及动态目标的RCS闪烁效应进行了详细的数学推导和分析，并讨论了微动目标雷达回波信号的微多普勒调制效应，以及动态RCS序列的周期与目标微动频率的关系。本章研究内容为后续的特征提取相关技术的研究奠定了基础。
第三章研究了基于动态RCS特性的弹道导弹进动频率提取方法。首先分析了雷达测量系统对RCS特性的影响，并将目标的RCS闪烁效应处理为乘性随机过程，建立了详细的锥体导弹动态RCS观测模型。在此基础上提出了两种准最大似然估计方法提取导弹目标的进动频率，分别为乘性噪声最大似然估计和高斯最大似然估计法，推导了乘性噪声最大似然估计方法的克拉美罗界。仿真实验结果验证了考虑RCS闪烁效应的必要性，以及本章所提方法的鲁棒性和有效性。
第四章提出了一种基于雷达回波信号时频图纹理的周期性估计微多普勒调制频率的方法。该方法从现象学的角度在宏观上分析了带尾翼自旋导弹雷达回波信号时频图纹理的周期性与微多普勒调制频率的关系。借鉴图像处理中纹理分析的思路，将时频谱图看成图像，结合二维傅里叶变换和自相关算法提取其纹理的周期，进而实现了对导弹目标微动频率的估计。该方法不受雷达观测姿态角度的影响，易于工程实现，且计算量较小，适用于先验知识较少的情况下对微动频率的提取。仿真实验验证了该方法的有效性，且在低信噪比条件下仍然适用。
第五章从节约导弹防御系统时间资源和有效利用雷达测量数据的角度出发，研究了基于分段非均匀雷达观测数据提取微动导弹目标的进动频率参数和散射中心位置信息的方法。根据导弹目标在高频区的电磁散射中心具有稀疏性这一特点，构造了包含进动频率的稀疏成份分析含参字典族，并建立了雷达回波信号的稀疏表征模型。在此基础上，将非线性最小二乘拟合和正交匹配追踪算法相结合，对进动导弹的雷达回波信号进行了稀疏重构，进而提取了导弹的进动频率和散射中心相对位置信息。该方法为导弹防御系统时间资源受限条件下的目标特征提取和识别技术提供了一种解决思路。
论文最后对研究内容进行了总结并给出了进一步研究方向。
Mid-course phase is the one that is most attractive for interception of a ballistic mis-sile (BM) warhead. However decoy releasing makes this phase of the flight the mostdifficult for target discrimination. Extracting appropriate feature parameters from radarreturns is a key technique in radar target discrimination of a BM. The aim of this paperis to analyze the micro-Doppler features of ballistic missiles during flight, and investigatemethods to extract the appropriate feature parameters.
InChapterOne, thedevelopmentstatusofthetargetdiscriminationtechnologyoftheBM is reviewed firstly. And then the characteristics and challenges of the technology inthe mid-course phase are briefly introduced. The main methods of the feature extractionand target discrimination of the BM in the mid-course phase are summarized as well. Themajor contributions of this dissertation are listed at the end of this chapter.
In Chapter Two, the geometric model of the BM observing by a radar is establishedsystematically. The shield effect of the spinning BM and the dynamic RCS scintillationare deduced in detail. The micro-Doppler effect of the radar echo from a BM with micro-motion is investigated, and the relationship between the the RCS sequence period and theprecession frequency of the BM is discussed. The study in this chapter is the foundationof the following research on the feature extraction of the BM targets.
In Chapter Three, the research mainly focuses on the precession frequency estima-tion based on the BM dynamic radar cross section (RCS) sequence. Firstly the influencesof the radar measure system to the RCS distribution is derived. The scintillation effectis taken into account and modeled as a multiplicative noise. And then the dynamic RCSdistribution model of a precessing conical missile is established. Two pseudo maximumlikelihoodestimation(MLE)approachestoextracttheparameterofmissileprecessionfre-quency are proposed. The first approach ignores the additive noise (i.e., assuming the in-finite signal-to-noise ratio (SNR)). The second approach enforces a Gaussian distributionon both additive and multiplicative noise components. The Cram′er-Rao Lower Bound(CRLB) corresponding to the maximum SNR scenario is derived. Simulations indicatethat accounting for the multiplicative noise in the estimation significantly improves esti-mationperformance,andalsoshowtherobustnessandvalidationoftheproposedmethods.
In Chapter Four, a method to estimated the micro-Doppler modulation frequencythroughanalyzingtheperiodicstructureoftheresultingtime-frequencydistribution(TFD)spectrogram is presented. The relationship between the texture period of the TFD ofa spinning BM and the micro-Doppler modulation frequency is analyzed from the phe-nomenology perspective. Based on the texture analysis in the image processing theory,the resultant TFD spectrogram is treated as an image (with periodic features along thetime axis). The2-D DFT (followed by autocorrelation) is then used to exploit the wellknown periodicity of the micro-Doppler signature in the TF domain, to better estimate themicro-Doppler modulation frequency via a simple cost effective and system friendly way.The method presented in this chapter has low computational cost, and does not need anyprior information about the signals, which satisfies the special demands of a BM targetrecognition system. The simulation results also indicate that the method work well underthe conditions of low signal to noise ratio (SNR).
In Chapter Five, aiming at saving the time resources in the ballistic missile defense(BMD) system and taking full advantage of radar measurements, a feature estimationmethod through a set of non-uniformly sampled radar signal is investigated. The esti-matedfeaturesincludethetheprecessionfrequencyandthescatteringcenters'distributioninformation of a BM with micro-motion. According to the sparsity nature of the BM scat-tering centers in the high frequency region, the parametric dictionary based on the sparsecomponent analysis (SCA) theory is constructed and the radar signal sampling model isestablished. And then, the algorithms of the nonlinear least square (NLLS) and the or-thogonal matching pursuit (OMP) are jointly employed to reconstruct the radar signal.Therefore, the precession frequency and the scattering centers' location of the precess-ing BM are estimated according to the sparse representation of the signal. The methodproposes a new notion for the feature extraction of the BM target under the restriction oflimited time resource in the ballistic missile defense system.
In Chapter Six, the work of the dissertation is summarized and the related furtherresearch is discussed.
引文
[1] Cepek R J. Ground-Based Midcourse Defense: Continue Testing, but OperationalFielding Must Take a Backseat to Theater Missile Defense and Homeland Secu-rity[D]. USA: Joint Forces Staff College, Joint Advanced Warfighting School,2005.
[2] BMDR. Ballistic Missile Defense Review Report[C]. USA: Department of De-fense,2010.
[3] Leon A. Tracking and Clasification of Boost Phase Ballistic Missile[D]. MIT: MITLincoln Laboratory,1995.
[4] Welch L D, Graham W. Missile Defense, Phase III: Modeling and Simulation[C].Defense Pentagon, Washington DC: Defense Science Board,2004.
[5] WrightD,GronlundL. DecoysandDiscriminationinInterceptTestIFT-8[J]. Unionof Concerned Scientists Working Paper,2002.
[6]马梁.弹道中段目标微动特性及综合识别方法[D].湖南长沙:国防科学技术大学,2011.
[7] Gansler J S. Ballistic Missile Defense Past and Future[C]. Washington: NationalDefense University, Center for Technology and National Security Policy,2010.
[8]维利卡洛夫.弹道导弹突防中的电子对抗[M].成都:信息产业部电子29所,2000.
[9] T. K, Campbell. Integrated Missile Defense[J]. JFQ,2007,46(3):64--65.
[10]黄培康.雷达目标特征信号[M].北京:宇航出版社,1993.
[11] Hildreth S A, Ek C. Long-Range Ballistic Missile Defense in Europe[J]. Congres-sional Research Service Report for Congress,2008, RL34051.
[12] Tanks D R. National Missile Defense: Policy Issues and Technological Capabili-ties[M]. Washington, USA: Svec Conway Inc.,2000.
[13] Samson V. Flight Tests for Ground-based Midcourse Defense (GMD) System[C].www.cdi.org,1154-1160: Center for Defense Information,2006.
[14] Gordon W B. Statistical Moments of Radar Cross Section[J]. IEEE Transcationson Antennas and Propagation,1993,41(4):506--508.
[15]冯德军.弹道中段目标雷达识别与评估研究[D].湖南长沙:国防科学技术大学,2006.
[16] GAO. Missile Defense: Review of Results and Limitations of an Early NationalMissile Defense Flight Test[C]. Defense Pentagon, Washington DC: General Ac-counting Office,2002，第GAO-02-124卷.
[17] GAO. Missile Defense: Review of Allegations about an Early National MissileDefense Fight Test[C]. Defense Pentagon, Washington DC: General AccountingOffice,2002，第GAO-02-125卷.
[18] Foster T. Application of Pattern Recognition Techniques for Early Warning Radar(EWR) Discrimination[C]. Ground-Based Midcourse Defense Joint Program Of-fice: U.A. Army Space and Missile Defense Command,1995，第ADA298895卷.
[19] R.Lambour, Morgan T. Assessment Orbital Debris Size Estimation From RadarCrossSectionMeasurements[C]. USA:CoreTechnologiesforSpaceSystemsCon-ference,2001.
[20] R. L, N. R, K.T.M.I. Assessment of Orbital Debris Size Estimation From RadarCross Section Measurements[J]. Adr. Space Res.,2004,34.
[21] Rasmussen J L, Haupt R L, Walker M L. RCS Feature Extraction from SimpleTargets Using Time-Frequency Analysis[C]. USA: SPIE,1996.
[22]丁小峰.基于窄带信息的弹道中段目标特性反演技术研究[D].湖南长沙:国防科学技术大学,2011.
[23]吕金建，丁健江，项清.弹道导弹识别技术发展综述[J].探测与控制学报,2010,32(4):7--14.
[24] J. L H, H. Y S. Using Range Profile as Feature Vectors to Identify AerospaceObject[J]. IEEE Trans. on Antennas and Propagation,1993,41(3):261--268.
[25] K.W. Non-cooperative TargetRecognition in the Frequency Domain[J]. IEE Proc-Radar, Sonar And Nacigation,2004,151(2):77--84.
[26] E J R, D R N, M K C. A Radar Target Discrimination Scheme Using the Dis-crete Wavelet Transfotm for Reduced Data Storage[J]. IEEE Trans. on AP,1994,42(7):1033--1037.
[27] Webb R A. Gamma Mixture Models for Target Recognition[M]. Germany:Mannheim,1998.
[28] A. M R, J. W J. Statiscal Feature Based HRR Radar Classification[M]. Germany:Mannheim,1998.
[29]刘永祥.导弹防御系统中的雷达目标综合识别研究[D].湖南长沙:国防科学技术大学,2004.
[30] W. A, Rihaczek, J. S. Theory and Practice of Radar Target Identification[M].[S.l.]:Artech House.
[31] Camp W W, Mayhan J T, O'Donnell R M. Wideband Radar for Ballistic MissileDefense and Range-doppler Imaging of Satellite[J]. Lincoln Laboratory Journal,2000,12(2):267--280.
[32] P.E. Y D B, B. H. Eigenspace-Based Motion Compensation for ISAR Target Imag-ing[J].
[33] T. S, S. H. Estimation and Correction of Complex Target Motion Effects in InverseSynthetic Imaging of Aircraft[C]. USA: IEEE International Radar Conference,2000.
[34] Z. B, Y. S G, D. X M. Time-Frequency Approaches to ISAR Imaging of Maneuver-ingTargetandTheirLimitaions[J]. IEEETransactionsonAerospaceandElectronicSystems,2001,37(3):1092--1099.
[35] S.B. C, S.J. D, B. C. Sepatation of Target Rigid Body and Micro-Doppler Effects inISAR Imaging[J]. IEEE Transactions on Aerospace and Electronic Systems,2006,42(4):1496--1506.
[36] D. P, A. M, A. A. Motion Estimation and Optimum Time Selection for Ship ISARImaging[C]. Monterey: IEEE Radar Conference,2003.
[37] F. B, D. M E, M. D. High-resolution ISAR Imaging of Maneuvering Targets byMeans of the Range Instantaneous Doppler Technique: Modeling and PerformanceAnalysis[J]. IEEE Transactions on Imaging Processing,2001,10(12):1880--1890.
[38] Mayhan J, Burrows M, Cuomo K. High resolution3D "snapshot" ISAR Imagingand Feature Extraction[J]. IEEE Transactions on Aerospace and Electronic Sys-tems,2001,37(2):630--641.
[39] Stiefel E, Scheifele G. Linear and Regular Celestial Mechanics. Perturbed Two-body Motion.Numerical methods[M]. New York: Canonical theory,1975.
[40]郗晓宁，王威.近地航天器轨道基础[M].长沙:国防科技大学出版社,2003.
[41]赵艳丽，王雪松，饶彬，王国玉.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.
[42]唐毓燕，黄培康.基于高精度径向测速的宽带雷达单诱饵速度识别法[J].宇航学报,2006,27(4):659--663.
[43]刘丽华.弹道导弹中段雷达特性分析与提取方法研究[D].湖南长沙:国防科学技术大学,2006.
[44] An F, Xu X. Real-Time ISAR Image Synthesis of Ballistic Targets[C].[S.l.]: IEEEInternational Symposium on Microwave, Antenna, Propagation and EMC Tech-nologies for Wireless Communications Proceedings,2005.
[45] Chen V C. Micro-Doppler Effect of Micro-motion Dynamics A Review[C].[S.l.]:SPIE,2003.
[46] Schultz K, Davidson S, Stein A,等. Range Doppler Laser Radar for MidcourseDiscrimination-The Firefly Experiments[C]. Albuquerque,NM: AIAA,1993，第2卷:6--9.
[47] J.F. H. S-band Radar Micro-doppler Signatures for BMD Discrimination[C]USAMissile Defense Agency Small Business Innovation Research Program,.[S.l.]:MDA,2004.
[48] J.E. G, P. B. The Problem of Kill Assessment: The Doppler Effect and Exo-atmospheric Kill Assessment[C]. Edinburgh, UK: Proceedings of the IEEE In-ternational Radar Conference,2002.
[49] O. U L, L.A. T. Radars for the Detection and Tracking of Cruise Missiles[J]. TheLincoln Laboratory Journal,2000,12(2):355--366.
[50] for Naval Forces' Capability for Theater Missile Defense C. Naval Forces' Capabil-ity for Theater Missile Defense[M]. Washington,D.C.: National Academy Press,2001.
[51] Chen V, Li F, Ho S,等. Analysis of Micro-Doppler Signatures[J]. IEE ProceedingsRdadar Sonar and Navigation,2003,150(4):271--276.
[52] Chen V C, Li F, Ho S. Micro-doppler Effect in Radar: Phenomenon, Model andSimulation Study[J]. IEEE Transaction on AES,2006,42(1):2--21.
[53] Bell M R, Grubbs R A. JEM Modeling and Measurement for Radar Target Iden-tification[J]. IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONICSYSTEM,1993,29(1):73--87.
[54] Polycarpou A C, Balanis C A, Stefanov A. Helicopter Rotor-Blade Modulation ofAntenna Radiation Characteristics[J]. IEEE TRANSACTIONS ON ANTENNASAND PROPAGATION,2001,49(5):688--696.
[55] Clark M. High Range Resolution Techniques For Ballistic Missile[J]. BritishAerospace Land and Sea System,1999.
[56] Kulpa. Continuous Wave Radars-monostatic, Multistatic and Network[C]. Berlin,Germany: IEEE International Radar Symposium,2005.
[57] R. L, G. H. Modeling and Experimental Design for the On-Orbit Inertial ParameterIdentification of Free-Flying Space Robots[J]. ASME International Design En-gineering Technical Conferences and Computers and Information in EngineeringConference,2005.
[58]刘永祥，黎湘，庄钊文.空间目标进动特性及其在雷达目标识别中的应用[J].自然科学进展,2004,11(11):1329--1332.
[59] Tao W, Xuesong W. Estimation of Precession Parameters and Generation of ISARImages of Ballistic Missile Targets[J]. IEEE Trans. on AES.,2010,46(4):1983--1995.
[60]罗红.动态雷达目标的建模与识别研究[D].北京:航天科工集团公司第二研究院,2000.
[61]陈行勇.微动目标雷达特征提取技术研究[D].湖南长沙:国防科学技术大学,2006.
[62] S. H, R.M. L, K.J. P. On Estimating the Amplitude of Harmonic Vibration from theDoppler Spectrum of Reflected Signals[J]. Acoustical Society of America,1990,88(6):2702--2712.
[63] Y.Y,J.S,T.S. UltrasonicImagingofInternalVibrationofSoftTissueunderForcedVibration[J]. IEEE Trans on Ultrasonics, Ferroelectrics and Frequency Control,1990,37(2):45--53.
[64] M.R. B, R.A. G. JEM Modeling and Measurement for Radar Target Identifica-tion[J]. IEEE Trans. on Aerospace and Electronic Systems,,1993,29(1):73--87.
[65] P. S, M. A, F. A. Analysis of Micro-Doppler Signals Using Linear FM BasisDecomposition[C].[S.l.]: Proceedings on Radar Sensor Technology,2006.
[66] P. S, M. A, T. T. Micro-Doppler Signal Estimation for Vibrating and RotatingTargets[C]Proceedings of the8th International Symposium on Signal Processingand Its Applications. Orlando, USA: SPIE,2005.
[67] Chen V C, HaoLing. Time-Frequency Transforms for Radar Imaging and SignalAnalysis[M]. Boston, London: Artech House,2002.
[68] P. S, M. A, F. A. Urban Target Classifications Using Time-frequency Micro-Doppler Signatures[C]. Monterey, USA: The9th International Symposium on Sig-nal Processing and Its Applications,2007.
[69] V.C. C, Lipps. Time-frequency Signatures of Micro-Doppler Phenomenon forFeature Extraction[C].[S.l.]: Proceedings of SPIE,2000.
[70] Lei J. Recognition Based on Time-Frequency Distributions of Radar Micro-Doppler Dynamics[C]. Washington DC: SNPD/SAWN,2005.
[71] S.L. M, C. M, S. S. Large Dynamic Range Time-frequency Signal Analysis withApplication to Helicopter Doppler Radar Data[C].[S.l.]: SPIE proceedings on Ad-vanced Signal Processing Algorithms, Architectures, and Implements,2003.
[72] Thayaparan T, Abrol S, Riseborough E. Micro-Doppler Radar Signatures for In-telligent Target Recognition[C]DRDC Ottawa Technical Memorandum. Ottawa,Canada: Defence Research and Development Cananda-Ottawa,2006.
[73] T. T, L.J. S, M. D. Micro-Doppler Parameter Estimation from A Fraction of thePeriod[J].
[74]李康乐.雷达目标微动特征提取与估计技术研究[D].湖南长沙:国防科学技术大学,2010.
[75]刘进.微动目标雷达信号参数估计与物理特征提取[D].湖南长沙:国防科学技术大学,2010.
[76] Chen V C. Spatial and Temporal Independent Component Analysis of Micro-Doppler Features[C]. Rome, Italy: International Radar Conference,2005.
[77] J. L, Hao L. Application of Adaptive Chirplet Representation for ISAR FeatureExtraction from Targets with Rotating Parts[J]. IEE Proceedings on Radar, Sonarand Navigation,2003,150(4):284--291.
[78] J. L. Model-based Signal Processing for Radar Imaging of Targets with ComplexMotions[D]. Texas: University of Texas at Austin,2002.
[79] Thayaparan T, Abrol S, Qian S. Micro-Doppler Analysis of Rotating Target inSAR[C]DRDC Ottawa Technical Memorandum. Ottawa, Canada: Defence Re-search and Development Cananda-Ottawa,2005.
[80]金光虎.中段弹道目标ISAR成像及物理特性反演技术研究[D].湖南长沙:国防科学技术大学,2009.
[81]黄培康，殷红成，许小剑.雷达目标识别特性[M].北京:电子工业出版社,2005.
[82]王保义，时振栋.电磁场在目标识别中的应用[M].北京:电子工业出版社,1995.
[83] Bechtel M. Short-pulse Target Characteristics[C]Atmospheric effects on radartarget identification and imaging. Goslar, West Germany: Proceedings of the Ad-vanced Study Institute,1976，第A77-24876卷:3--53.
[84] Bin R, YanLi Z, Shunping X,等. Discrimination of exo-atmospheric active de-coys using acceleration information[J]. IET Radar, Sonar and Navigation,2010,4(4):626--638.
[85]王国雄.弹头技术[M].北京:宇航出版社,1993.
[86]郦苏丹，任萱.大气层外诱饵释放研究[J].宇航学报,2001,22(2):100--105.
[87] Boutelle J, Kau S, Marino J. ICBM Reentry Vehicle Navigation System Devel-opment at Honeywell[J]. Position Location and Navigation Symposium,1998,150(2):294--302.
[88] CrawfordJ,PearsonJ. GroundBasedRadarInteroperabilityandInterfaceRequire-ments for the Ballistic Missile Defense of Conus[C].[S.l.]: AIAA,1993.
[89] EliasR,NevarezJV. ActiveNutationadnPrecessionControlforExoatomosphericSpinning Ballistic Missiles[C]AIAA Guidance, Navigation and Control Confer-ence and Exhibit. Honolulu, Hawaii: AIAA,2008，第AIAA2008-6998卷.
[90] Li K, Jiang W, Liu Y. Feature Extraction of Cone with Precession Based on Micro-Doppler[C]IET International Radar Conference. Guilin, China: IET,2009，第1卷:1--5.
[91] Gerry M, Potter L, Gupta I,等. A Parametric Model for Synthetic ApertureRadar Measurements[J]. IEEE Transactions on Antennas and Propagation,1999,47(7):1179--1188.
[92] Jouny I. Compressed Sensing for UWB Radar Target Signature Reconstruction[C].ECE Dept., Latfayette College, Easton, PA: IEEE,2009.
[93] J.B. K. Geometrical Theory of Diffraction[J]. Journal of Opt. Soc. Am,1962,52(2):116--118.
[94]胡俊豪，许小剑，毛京红.复杂目标多点源模型及其应用[J].目标与环境特性研究,1997,4.
[95] S. S, P. G, C. B. Complex Target Signature Generation[J]. Proceeding of ICSP,1996,4.
[96] Potter L, Moses R. Attributed Scattering Centers for SAR ATR[J]. IEEE Transac-tions on Image Processing,1997,6(1):79--91.
[97] Lee S H. Investigation of the Effects of Target Feature Variations on Ballistic Mis-sile RCS[D]. USA: Graduate School of Engineering and Management,Air ForceInstitute of Technology,2006.
[98] Xu X, Narayanan R. Three-dimensional Interferometric ISAR Imaging for TargetScattering Diagnosis and Modeling[J]. IEEE Transactions on Image Processing,2001,10(7):1094--1102.
[99] Haroldsen, J. D. Navier-Stokes Computations of Finned Missiles at SupersonicSpeeds[C]. Denver, USA: AIAA Applied Aerodynamics Conference and Exhibit,2000.
[100]张云飞，武哲，陆柱蕙.导弹的RCS计算研究[J].北京航空航天大学学报,2000,26(3):325--328.
[101] Knott E F, Shaeffer J F, Tuley M T. Radar Cross Section (Second Edition)[M].Ralergh, NC: SciTECH Publishing, INC.,2004.
[102] R.F. H. Time-Harmonic Electromagnetic Fields[M]. New York: McGraw-Hill,1968.
[103] J.J.B. ElectromagneticandAcousticScatteringbySimpleShapes[M]. Amsterdam:North-Holland Publishing,1969.
[104] Turner S D. Rapid Electromagnetic Scattering Predictor for Extremely ComplexTargets[J]. IEE Processings,1990,137(4).
[105] Volakls J L. A High Frequency Electromagnetic Scattering Prediction Code andEnvironmentforComplexThreeDimensionalObject[J]. IEEEAntennasandProp-agation Magazine,1994,36(1):65--69.
[106] MahafzaBR. RadarSystemsAnalysisandDegignUsingMATLAB[M]. Alabama:CRC Press,2000.
[107] Ross R A. Investigation of Scattering Principles, Volume III-Analytical Investiga-tion[R]. USA: Cornell Aeronautical Laboratory,1969.
[108]陈行勇，黎湘，郭桂蓉，姜斌.中段目标进动雷达特征提取[J].信号处理,2006,22(5):707--711.
[109]金文彬，刘永祥，任双桥，黎湘，庄钊文.锥体目标空间进动特性分析及其参数提取[J].宇航学报,2004,25(4):408--422.
[110]陈行勇，黎湘，郭桂蓉，姜斌.微进动弹道导弹目标雷达特征提取[J].电子与信息学报,2006,28(4):643--646.
[111] Maio A D, Farina A, Foglia G. Target fluctuation Models and Their Application toRadar Performance Prediction[J]. IEE Proceeding Radar Sonar Navigation,2004,151(5):261--269.
[112] Johnston S. Target Fluctuation Models for Radar System Design and PerformanceAnalysis: An Overwiew of Three Papers[J]. IEEE Transactions on Aerospace andElectronic Systems,1997,33(2):696--697.
[113]丁鹭飞，富录.雷达原理[M].西安:西安电子科技大学出版社,2002.
[114] Swerling P. Radar Probability of Detection for Some Additional Fluctuating Tar-get Cases[J]. IEEE Transactions on Aerospace and Electronic Systems,1997,22(2):698--709.
[115] Weinstock W. Target Cross Section Models for Radar System Analysis[D]. Penn-sylvania: University of Pennsylvania,1964.
[116] Meyer D P, Meyer H A. Radar Target Detection-Handbook of Theory and Prac-tice[M]. Alabama: Academic Press,1973.
[117] Ojha A K, Koch D B. Impact of Noise and Target Fluctuation on the performanceof Frank Polyphase Coded Radar Signals[C]The24th Southeastern Symposium onand The3rd Annual Symposium on Communications. Tennessee: System Theory,1992，第SSST/CSA92卷.
[118]赵宏钟，付强.基于循环平稳的复调频信号检测性能研究[J].电子学报,2004,32(6):942--945.
[119] Rutten M G, Gordon N J, Maskell S. Recursive Track-before-detect with Tar-get Amplitude Fluctuations[J]. IEE Processing on Radar Sonar Navigation,2005,152(5):345--352.
[120] Cumming I G, Wong F H. Digital Processing of Synthetic Aperture Radar Data--Algorithms and Implementation[M]. Canada: Artech House,2005.
[121] Martin J, Mulgrew B. Analysis of the theoretical radar return signal form air-craftpropeller blades[C]Record of the IEEE1990International Radar Conference.London, UK: IEEE,1990.
[122] MaioA,A.Farina, G.Foglia. NewTargetFluctuationModelsandTheirExperimen-tal Validation[J]. IEEE Transactions on Aerospace and Electronic Systems,1997,33(2):696--697.
[123] Skolnik M L. Radar Handbook,Third Edition[M]. USA: McGraw Hill Company,2008.
[124] Swami A. Cramer-Rao Bounds for Deterministic Signals in Additive and Multi-plicative Noise[J]. Signal Processing,1996,53(2):231--244.
[125] Ghogho M, Nandi A K, Swami A. Cramer-Rao Bounds and Maximum LikelihoodEstimation for Random Amplitude Phase-Modulated Signals[J]. IEEE Transactionon Signal Processing,1999,47(11):2905--2915.
[126] CurryG. RadarSystemPerformanceModeling[M]. BostonLondon: ArtechHouse,2005.
[127] Kay S M. Fundamentals of Statistical Signal Processing: Estimation Theory[M].New Jersey: Prentice Hall PTR,1993.
[128] Swerling P. Probability of Detection for Fluctuating Targets[J]. IRE Transactionson Information Theory,1960,6(2):269--308.
[129] CohenL. Time-frequencyAnalysis:TheoryandApplications[M]. NewYork,USA:PRENTICE HALL,1998.
[130] Baraniuk R G, Jones D L. A Signal-dependent Time-frequency Representation:Optimal Kernel Design[J]. IEEE Trans. on Signal Processing,1993,41(4):1589--16002.
[131] Baraniuk R G, Jones D L. A Signal-dependent Time-frequency Representation:Fast Algorithm for Optimal Kernal Design[J]. IEEE Trans. on Signal Processing,1994,42(1):134--146.
[132] Ouyang X, Amin M. Short-time Fourier Transform Reveiver for Nonstationary In-terference Excision in Direct Sequence Spread Spectrum Communication[J]. IEEETrans. on Signal Processing,2001,49(4):851--863.
[133] Durak L, Arikan O. Short-time Fourier Transform: Two Fundamental Propertiesand an Optimal Implementation[J]. IEEE Transactions on Signal Processing,2003,51(5):1231--1242.
[134] Nelson D. Signal Reconstruction from Concentrated STFT Peaks[C]IEEE Confer-ence on Acoustist Speech and Signal Processing. Philadelphia: IEEE,2005.
[135] Umapathy K, Krishnan S. Time-Width Versus Frequency Band Mapping of EnergyDistributions[J]. IEEE Transactions on Signal Processing,2007,55(3):978--989.
[136] Jones L D, Parks T W. A high resolution data-adaptive time-frequency represen-tation[J]. IEEE Transactions on Acoustics, Speech and Signal Processing,1990,38(12):2127--2135.
[137] Gonzalez R C, Woods R E, Eddins S L. Digital Image Processing (Second Edi-tion)[M]. Tennessee, USA: Prentice Hall,2002.
[138] Gonzalez R C, Woods R E. Digital Image Processing[M]. Beijing, China: Publish-ing House of Electronics Industry,2002.
[139]张光义，王德纯.空间探测相控阵雷达[M]. First.北京:科学出版社,2001.
[140] B. Z, N.K. B. Multi-target Tracking in Clutter: Fast Algorithms for Data Associa-tion[J]. IEEE Trans. on Aerospace and Electronic Systems,1993,29(2):352--363.
[141] Younghun J, Sunmog H. Modeling and Parameter Optimization of Agile BeamRadar Tracking[J]. IEEE Trans. on Aerospace and Electronic Systems,2003,39(1):12--33.
[142]刘兆磊，徐振来，张光义.基于多驻留测量的相控阵雷达目标跟踪算法[J].系统工程与电子技术,2006,28(3):376--379.
[143]孟建.分段采样信号的相位关联技术[J].系统工程与电子技术,2004,26(12):1784--1797.
[144]杜小勇.稀疏成份分析及在雷达成像处理中的应用[D].湖南长沙:国防科学技术大学,2005.
[145] M. V, P. M, T. B. Sampling Signals with Finite Rate of Innovation[J]. IEEE Trans.on Signal Processing,2002,50(6):1417--1428.
[146]刘吉英.压缩感知理论及在成像中的应用[D].湖南长沙:国防科学技术大学,2010.
[147] Muthukrishnan S. Data Streams: Algorithms and Applications[M]. Boston: NowPunlishers,2005.
[148] Blu T, Dragotti P, Vetterli M, et al. Sparse Sampling of Signal Innovations[J]. IEEESignal Processing Magazine,2008.
[149] G. M S, F. Z Z. Matching Pursuits with Time-frequency Dictionaries[J]. IEEETrans. on Signal Processing,1993,41(12):3397--3415.
[150] TroppJ. ComputaionalMethodsforSparseSolutionofLinearInverseProblems[C].Latfayette College: Proceedings of the IEEE,2009.
[151] ChenSS,DonohoDL,SaundersMA. AtomicDecompositionbyBasicPursuit[J].SIAM Journal on Scientific Computing,1998,20(1):33--61.
[152] McClure M R, Carin L. Matching Pursuits with a Wave-based Dictionary[J]. IEEETrans. on Signal Processing,1997,45(12):2912--2927.
[153] Tropp J A, Gilber A C. Signal Recovery From Random Measurements Via Or-thogonal Matching Pursuit[J]. IEEE Transactions on Information Theory,2007,53(12):4655--4666.
[154] Needell D, Vershynin R. Uniform Uncertainty Principle and Signal RecoveryVia Regularized Orthogonal Matching Pursuit[J]. Found. Comput Math.,2008,9(3):95--103.
[155] Needell D, Tropp J A. CoSaMP: Iterative Signal Recovery From Incomplete andInaccurate Samples[J]. Applied and Computational Harmonic Analysis,2009,26(1):301--321.
[156] Elad M, Bruckstein A. A Generalized Uncertainty Principle and Sparse Represen-tation in Pairs of Bases[J]. IEEE Trans. on Information Theory,2002,48(9):2558--2567.
[157] Gribonval R, Nielsen M. Sparse Representations in Unions of Bases[J]. IEEETrans. on Information Theory,2003,49(12):3320--3325.
[158] A Matlab Toolbox for Optimization Over Symmetric Cones[M].[S.l.]:[s.n.]. http://www.unimaas.nl/~sturm/papers/guide.ps.gz.
[159] Mathematical Programming System[M].[S.l.]:[s.n.]. http://www.mosek.com.
[160] l1-magic[M].[S.l.]:[s.n.]. http://www.acm.caltech.edu/l1magic/.
[161] SparseLab Software[M].[S.l.]:[s.n.]. http://sparselab.stanford.edu.
[162] PDCO:Primal-DualInteriorMethodforConvexObjectives[M].[S.l.]:[s.n.]. http://www.stanford.edu/group/SOL/software/pdco.html.
[163] Wright S, Nowak R, Figueiredo M. Sparse Reconstruction by Separable Approxi-mation[J]. IEEE Trans. on Signal Processing,2009,57.
[164] R. T. Regression Shrinkage and Selection Via the LASSO[J]. J.R.Statist. Soc. B,1996,58(1):267--288.
[165] R. C. Exact Reconstruction of Sparse Signals via Nonconvex Minimization[J].IEEE Signal Processing Letters,2007,14(10):707--710.
[166] E.J. C, M.B. W, S.P. B. Enhancing Sparsity by Reweighted l1Minimization[J]. J.Fourier Anal. Appl.,2008,14(5):877--905.
[167] E.G. L, Y. S. Linear Regression with a Sparse Parameter Vector[J]. IEEE Trans.on Signal Processing,2007,55(2):451--460.
[168] D.W,B.R. SparseBayesianLearningforBasisSelection[J]. IEEETrans.onSignalProcessing,2004,52(8):2153--2164.
[169] S. J, W. X, B. H, et al. Efficient Compressed Sensing Using Optimized ExpanderGraphs[J]. IEEE Trans. on Information Theory,2009,55(2):4299--4308.
[170] D.L. D, A. M, A. M. Message-passing Algorithms for Compressed Sensing[J].Proc. Natl. Acad. Sci.,2009,106(45):18914--18919.
[171] CandesE,TaoT. DecodingbyLinearProgramming[J]. IEEETrans.onInformationTheory,2006,51.
[172] Candes E, T.Tao. Near-optimal Signal Recovery From Random Projections:Universal Encoding Strategies?[J]. IEEE Trans. on Information Theory,2006,52(12):5406--5425.
[173] Baraniuk R G. Compressive Sensing[C].[S.l.]: Proceedings of the IEEE,2009.
[174] BaraniukR,DavenportM,DevoreR,等. ASimpleProofoftheRestrictedIsometryProperty for Random Matrics[J]. Constructive Approximation,2008,28(3):253--263.
[175] Zhang Y. A Simple Proof for Recoverability of l1-minimization: Go Over orUnder[C]Rice University CAAM Technical Report. Rice: Rice University,2005，第TR05-09卷.
[176] Cohen A, Dahmen W, DeVore R. Compressed Sensing and Best K-term Approxi-mation[J]. Journal of the American Mathematical Society,2009,22(1):211--231.
[177] Tropp J. Greed is good: Algorithmic Results for Sparse Approximation[J]. IEEETrans. on Information Theory,2006,50.
[178] KimKT,KimHT. Two-dimensionalScatteringCenterExtractionBasedonMulti-ple Elastic Modules Network[J]. IEEE Transactions on Antennas and Propagation,2003,51(4):848--861.
[179] Li K, Jiang W, Liu Y. Feature Extraction of Cone with Precession Based on Micro-Doppler[C]. Guilin, China: IET,2009.
[180] Swiger J M. Resolution Limits of Ultra Wideband Synthetic Aperture Radar Usinga Rectangular Aperture for FFT Processing[J]. IEEE Transactions on Aerospaceand Electronic Systems,1994,30(3):935--938.
[181] Elad M. Optimized Projections for Compressed Sensing[J]. IEEE Trans. on SignalProcessing,2007,12(1):5695--5702.
[182] Duarte-CarvajalinoJM,SapiroG. LearningtoSenseSparseSignals: SimultaneousSensing Matrix and Sparsifying Dictionary Optimization[J]. IEEE Trans. on ImageProcessing,2009,18(7):1395--1408.
[183] Ghogho M, Swami A, Nandi A. Nonlinear Least Squares Estimation for Har-monics in Multiplicative and Additive Noise[J]. Elsevier Signal Processing,1999,78(1):43--60.
[184] Agni-strategic Ballistic Missile[M].[S.l.]:[s.n.]. http://www.bharat-rakshak.com/land-forces/Equipment/Others/379-Agni-IRBM-(Page-1).html.
[2] BMDR. Ballistic Missile Defense Review Report[C]. USA: Department of De-fense,2010.
[3] Leon A. Tracking and Clasification of Boost Phase Ballistic Missile[D]. MIT: MITLincoln Laboratory,1995.
[4] Welch L D, Graham W. Missile Defense, Phase III: Modeling and Simulation[C].Defense Pentagon, Washington DC: Defense Science Board,2004.
[5] WrightD,GronlundL. DecoysandDiscriminationinInterceptTestIFT-8[J]. Unionof Concerned Scientists Working Paper,2002.
[6]马梁.弹道中段目标微动特性及综合识别方法[D].湖南长沙:国防科学技术大学,2011.
[7] Gansler J S. Ballistic Missile Defense Past and Future[C]. Washington: NationalDefense University, Center for Technology and National Security Policy,2010.
[8]维利卡洛夫.弹道导弹突防中的电子对抗[M].成都:信息产业部电子29所,2000.
[9] T. K, Campbell. Integrated Missile Defense[J]. JFQ,2007,46(3):64--65.
[10]黄培康.雷达目标特征信号[M].北京:宇航出版社,1993.
[11] Hildreth S A, Ek C. Long-Range Ballistic Missile Defense in Europe[J]. Congres-sional Research Service Report for Congress,2008, RL34051.
[12] Tanks D R. National Missile Defense: Policy Issues and Technological Capabili-ties[M]. Washington, USA: Svec Conway Inc.,2000.
[13] Samson V. Flight Tests for Ground-based Midcourse Defense (GMD) System[C].www.cdi.org,1154-1160: Center for Defense Information,2006.
[14] Gordon W B. Statistical Moments of Radar Cross Section[J]. IEEE Transcationson Antennas and Propagation,1993,41(4):506--508.
[15]冯德军.弹道中段目标雷达识别与评估研究[D].湖南长沙:国防科学技术大学,2006.
[16] GAO. Missile Defense: Review of Results and Limitations of an Early NationalMissile Defense Flight Test[C]. Defense Pentagon, Washington DC: General Ac-counting Office,2002，第GAO-02-124卷.
[17] GAO. Missile Defense: Review of Allegations about an Early National MissileDefense Fight Test[C]. Defense Pentagon, Washington DC: General AccountingOffice,2002，第GAO-02-125卷.
[18] Foster T. Application of Pattern Recognition Techniques for Early Warning Radar(EWR) Discrimination[C]. Ground-Based Midcourse Defense Joint Program Of-fice: U.A. Army Space and Missile Defense Command,1995，第ADA298895卷.
[19] R.Lambour, Morgan T. Assessment Orbital Debris Size Estimation From RadarCrossSectionMeasurements[C]. USA:CoreTechnologiesforSpaceSystemsCon-ference,2001.
[20] R. L, N. R, K.T.M.I. Assessment of Orbital Debris Size Estimation From RadarCross Section Measurements[J]. Adr. Space Res.,2004,34.
[21] Rasmussen J L, Haupt R L, Walker M L. RCS Feature Extraction from SimpleTargets Using Time-Frequency Analysis[C]. USA: SPIE,1996.
[22]丁小峰.基于窄带信息的弹道中段目标特性反演技术研究[D].湖南长沙:国防科学技术大学,2011.
[23]吕金建，丁健江，项清.弹道导弹识别技术发展综述[J].探测与控制学报,2010,32(4):7--14.
[24] J. L H, H. Y S. Using Range Profile as Feature Vectors to Identify AerospaceObject[J]. IEEE Trans. on Antennas and Propagation,1993,41(3):261--268.
[25] K.W. Non-cooperative TargetRecognition in the Frequency Domain[J]. IEE Proc-Radar, Sonar And Nacigation,2004,151(2):77--84.
[26] E J R, D R N, M K C. A Radar Target Discrimination Scheme Using the Dis-crete Wavelet Transfotm for Reduced Data Storage[J]. IEEE Trans. on AP,1994,42(7):1033--1037.
[27] Webb R A. Gamma Mixture Models for Target Recognition[M]. Germany:Mannheim,1998.
[28] A. M R, J. W J. Statiscal Feature Based HRR Radar Classification[M]. Germany:Mannheim,1998.
[29]刘永祥.导弹防御系统中的雷达目标综合识别研究[D].湖南长沙:国防科学技术大学,2004.
[30] W. A, Rihaczek, J. S. Theory and Practice of Radar Target Identification[M].[S.l.]:Artech House.
[31] Camp W W, Mayhan J T, O'Donnell R M. Wideband Radar for Ballistic MissileDefense and Range-doppler Imaging of Satellite[J]. Lincoln Laboratory Journal,2000,12(2):267--280.
[32] P.E. Y D B, B. H. Eigenspace-Based Motion Compensation for ISAR Target Imag-ing[J].
[33] T. S, S. H. Estimation and Correction of Complex Target Motion Effects in InverseSynthetic Imaging of Aircraft[C]. USA: IEEE International Radar Conference,2000.
[34] Z. B, Y. S G, D. X M. Time-Frequency Approaches to ISAR Imaging of Maneuver-ingTargetandTheirLimitaions[J]. IEEETransactionsonAerospaceandElectronicSystems,2001,37(3):1092--1099.
[35] S.B. C, S.J. D, B. C. Sepatation of Target Rigid Body and Micro-Doppler Effects inISAR Imaging[J]. IEEE Transactions on Aerospace and Electronic Systems,2006,42(4):1496--1506.
[36] D. P, A. M, A. A. Motion Estimation and Optimum Time Selection for Ship ISARImaging[C]. Monterey: IEEE Radar Conference,2003.
[37] F. B, D. M E, M. D. High-resolution ISAR Imaging of Maneuvering Targets byMeans of the Range Instantaneous Doppler Technique: Modeling and PerformanceAnalysis[J]. IEEE Transactions on Imaging Processing,2001,10(12):1880--1890.
[38] Mayhan J, Burrows M, Cuomo K. High resolution3D "snapshot" ISAR Imagingand Feature Extraction[J]. IEEE Transactions on Aerospace and Electronic Sys-tems,2001,37(2):630--641.
[39] Stiefel E, Scheifele G. Linear and Regular Celestial Mechanics. Perturbed Two-body Motion.Numerical methods[M]. New York: Canonical theory,1975.
[40]郗晓宁，王威.近地航天器轨道基础[M].长沙:国防科技大学出版社,2003.
[41]赵艳丽，王雪松，饶彬，王国玉.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.
[42]唐毓燕，黄培康.基于高精度径向测速的宽带雷达单诱饵速度识别法[J].宇航学报,2006,27(4):659--663.
[43]刘丽华.弹道导弹中段雷达特性分析与提取方法研究[D].湖南长沙:国防科学技术大学,2006.
[44] An F, Xu X. Real-Time ISAR Image Synthesis of Ballistic Targets[C].[S.l.]: IEEEInternational Symposium on Microwave, Antenna, Propagation and EMC Tech-nologies for Wireless Communications Proceedings,2005.
[45] Chen V C. Micro-Doppler Effect of Micro-motion Dynamics A Review[C].[S.l.]:SPIE,2003.
[46] Schultz K, Davidson S, Stein A,等. Range Doppler Laser Radar for MidcourseDiscrimination-The Firefly Experiments[C]. Albuquerque,NM: AIAA,1993，第2卷:6--9.
[47] J.F. H. S-band Radar Micro-doppler Signatures for BMD Discrimination[C]USAMissile Defense Agency Small Business Innovation Research Program,.[S.l.]:MDA,2004.
[48] J.E. G, P. B. The Problem of Kill Assessment: The Doppler Effect and Exo-atmospheric Kill Assessment[C]. Edinburgh, UK: Proceedings of the IEEE In-ternational Radar Conference,2002.
[49] O. U L, L.A. T. Radars for the Detection and Tracking of Cruise Missiles[J]. TheLincoln Laboratory Journal,2000,12(2):355--366.
[50] for Naval Forces' Capability for Theater Missile Defense C. Naval Forces' Capabil-ity for Theater Missile Defense[M]. Washington,D.C.: National Academy Press,2001.
[51] Chen V, Li F, Ho S,等. Analysis of Micro-Doppler Signatures[J]. IEE ProceedingsRdadar Sonar and Navigation,2003,150(4):271--276.
[52] Chen V C, Li F, Ho S. Micro-doppler Effect in Radar: Phenomenon, Model andSimulation Study[J]. IEEE Transaction on AES,2006,42(1):2--21.
[53] Bell M R, Grubbs R A. JEM Modeling and Measurement for Radar Target Iden-tification[J]. IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONICSYSTEM,1993,29(1):73--87.
[54] Polycarpou A C, Balanis C A, Stefanov A. Helicopter Rotor-Blade Modulation ofAntenna Radiation Characteristics[J]. IEEE TRANSACTIONS ON ANTENNASAND PROPAGATION,2001,49(5):688--696.
[55] Clark M. High Range Resolution Techniques For Ballistic Missile[J]. BritishAerospace Land and Sea System,1999.
[56] Kulpa. Continuous Wave Radars-monostatic, Multistatic and Network[C]. Berlin,Germany: IEEE International Radar Symposium,2005.
[57] R. L, G. H. Modeling and Experimental Design for the On-Orbit Inertial ParameterIdentification of Free-Flying Space Robots[J]. ASME International Design En-gineering Technical Conferences and Computers and Information in EngineeringConference,2005.
[58]刘永祥，黎湘，庄钊文.空间目标进动特性及其在雷达目标识别中的应用[J].自然科学进展,2004,11(11):1329--1332.
[59] Tao W, Xuesong W. Estimation of Precession Parameters and Generation of ISARImages of Ballistic Missile Targets[J]. IEEE Trans. on AES.,2010,46(4):1983--1995.
[60]罗红.动态雷达目标的建模与识别研究[D].北京:航天科工集团公司第二研究院,2000.
[61]陈行勇.微动目标雷达特征提取技术研究[D].湖南长沙:国防科学技术大学,2006.
[62] S. H, R.M. L, K.J. P. On Estimating the Amplitude of Harmonic Vibration from theDoppler Spectrum of Reflected Signals[J]. Acoustical Society of America,1990,88(6):2702--2712.
[63] Y.Y,J.S,T.S. UltrasonicImagingofInternalVibrationofSoftTissueunderForcedVibration[J]. IEEE Trans on Ultrasonics, Ferroelectrics and Frequency Control,1990,37(2):45--53.
[64] M.R. B, R.A. G. JEM Modeling and Measurement for Radar Target Identifica-tion[J]. IEEE Trans. on Aerospace and Electronic Systems,,1993,29(1):73--87.
[65] P. S, M. A, F. A. Analysis of Micro-Doppler Signals Using Linear FM BasisDecomposition[C].[S.l.]: Proceedings on Radar Sensor Technology,2006.
[66] P. S, M. A, T. T. Micro-Doppler Signal Estimation for Vibrating and RotatingTargets[C]Proceedings of the8th International Symposium on Signal Processingand Its Applications. Orlando, USA: SPIE,2005.
[67] Chen V C, HaoLing. Time-Frequency Transforms for Radar Imaging and SignalAnalysis[M]. Boston, London: Artech House,2002.
[68] P. S, M. A, F. A. Urban Target Classifications Using Time-frequency Micro-Doppler Signatures[C]. Monterey, USA: The9th International Symposium on Sig-nal Processing and Its Applications,2007.
[69] V.C. C, Lipps. Time-frequency Signatures of Micro-Doppler Phenomenon forFeature Extraction[C].[S.l.]: Proceedings of SPIE,2000.
[70] Lei J. Recognition Based on Time-Frequency Distributions of Radar Micro-Doppler Dynamics[C]. Washington DC: SNPD/SAWN,2005.
[71] S.L. M, C. M, S. S. Large Dynamic Range Time-frequency Signal Analysis withApplication to Helicopter Doppler Radar Data[C].[S.l.]: SPIE proceedings on Ad-vanced Signal Processing Algorithms, Architectures, and Implements,2003.
[72] Thayaparan T, Abrol S, Riseborough E. Micro-Doppler Radar Signatures for In-telligent Target Recognition[C]DRDC Ottawa Technical Memorandum. Ottawa,Canada: Defence Research and Development Cananda-Ottawa,2006.
[73] T. T, L.J. S, M. D. Micro-Doppler Parameter Estimation from A Fraction of thePeriod[J].
[74]李康乐.雷达目标微动特征提取与估计技术研究[D].湖南长沙:国防科学技术大学,2010.
[75]刘进.微动目标雷达信号参数估计与物理特征提取[D].湖南长沙:国防科学技术大学,2010.
[76] Chen V C. Spatial and Temporal Independent Component Analysis of Micro-Doppler Features[C]. Rome, Italy: International Radar Conference,2005.
[77] J. L, Hao L. Application of Adaptive Chirplet Representation for ISAR FeatureExtraction from Targets with Rotating Parts[J]. IEE Proceedings on Radar, Sonarand Navigation,2003,150(4):284--291.
[78] J. L. Model-based Signal Processing for Radar Imaging of Targets with ComplexMotions[D]. Texas: University of Texas at Austin,2002.
[79] Thayaparan T, Abrol S, Qian S. Micro-Doppler Analysis of Rotating Target inSAR[C]DRDC Ottawa Technical Memorandum. Ottawa, Canada: Defence Re-search and Development Cananda-Ottawa,2005.
[80]金光虎.中段弹道目标ISAR成像及物理特性反演技术研究[D].湖南长沙:国防科学技术大学,2009.
[81]黄培康，殷红成，许小剑.雷达目标识别特性[M].北京:电子工业出版社,2005.
[82]王保义，时振栋.电磁场在目标识别中的应用[M].北京:电子工业出版社,1995.
[83] Bechtel M. Short-pulse Target Characteristics[C]Atmospheric effects on radartarget identification and imaging. Goslar, West Germany: Proceedings of the Ad-vanced Study Institute,1976，第A77-24876卷:3--53.
[84] Bin R, YanLi Z, Shunping X,等. Discrimination of exo-atmospheric active de-coys using acceleration information[J]. IET Radar, Sonar and Navigation,2010,4(4):626--638.
[85]王国雄.弹头技术[M].北京:宇航出版社,1993.
[86]郦苏丹，任萱.大气层外诱饵释放研究[J].宇航学报,2001,22(2):100--105.
[87] Boutelle J, Kau S, Marino J. ICBM Reentry Vehicle Navigation System Devel-opment at Honeywell[J]. Position Location and Navigation Symposium,1998,150(2):294--302.
[88] CrawfordJ,PearsonJ. GroundBasedRadarInteroperabilityandInterfaceRequire-ments for the Ballistic Missile Defense of Conus[C].[S.l.]: AIAA,1993.
[89] EliasR,NevarezJV. ActiveNutationadnPrecessionControlforExoatomosphericSpinning Ballistic Missiles[C]AIAA Guidance, Navigation and Control Confer-ence and Exhibit. Honolulu, Hawaii: AIAA,2008，第AIAA2008-6998卷.
[90] Li K, Jiang W, Liu Y. Feature Extraction of Cone with Precession Based on Micro-Doppler[C]IET International Radar Conference. Guilin, China: IET,2009，第1卷:1--5.
[91] Gerry M, Potter L, Gupta I,等. A Parametric Model for Synthetic ApertureRadar Measurements[J]. IEEE Transactions on Antennas and Propagation,1999,47(7):1179--1188.
[92] Jouny I. Compressed Sensing for UWB Radar Target Signature Reconstruction[C].ECE Dept., Latfayette College, Easton, PA: IEEE,2009.
[93] J.B. K. Geometrical Theory of Diffraction[J]. Journal of Opt. Soc. Am,1962,52(2):116--118.
[94]胡俊豪，许小剑，毛京红.复杂目标多点源模型及其应用[J].目标与环境特性研究,1997,4.
[95] S. S, P. G, C. B. Complex Target Signature Generation[J]. Proceeding of ICSP,1996,4.
[96] Potter L, Moses R. Attributed Scattering Centers for SAR ATR[J]. IEEE Transac-tions on Image Processing,1997,6(1):79--91.
[97] Lee S H. Investigation of the Effects of Target Feature Variations on Ballistic Mis-sile RCS[D]. USA: Graduate School of Engineering and Management,Air ForceInstitute of Technology,2006.
[98] Xu X, Narayanan R. Three-dimensional Interferometric ISAR Imaging for TargetScattering Diagnosis and Modeling[J]. IEEE Transactions on Image Processing,2001,10(7):1094--1102.
[99] Haroldsen, J. D. Navier-Stokes Computations of Finned Missiles at SupersonicSpeeds[C]. Denver, USA: AIAA Applied Aerodynamics Conference and Exhibit,2000.
[100]张云飞，武哲，陆柱蕙.导弹的RCS计算研究[J].北京航空航天大学学报,2000,26(3):325--328.
[101] Knott E F, Shaeffer J F, Tuley M T. Radar Cross Section (Second Edition)[M].Ralergh, NC: SciTECH Publishing, INC.,2004.
[102] R.F. H. Time-Harmonic Electromagnetic Fields[M]. New York: McGraw-Hill,1968.
[103] J.J.B. ElectromagneticandAcousticScatteringbySimpleShapes[M]. Amsterdam:North-Holland Publishing,1969.
[104] Turner S D. Rapid Electromagnetic Scattering Predictor for Extremely ComplexTargets[J]. IEE Processings,1990,137(4).
[105] Volakls J L. A High Frequency Electromagnetic Scattering Prediction Code andEnvironmentforComplexThreeDimensionalObject[J]. IEEEAntennasandProp-agation Magazine,1994,36(1):65--69.
[106] MahafzaBR. RadarSystemsAnalysisandDegignUsingMATLAB[M]. Alabama:CRC Press,2000.
[107] Ross R A. Investigation of Scattering Principles, Volume III-Analytical Investiga-tion[R]. USA: Cornell Aeronautical Laboratory,1969.
[108]陈行勇，黎湘，郭桂蓉，姜斌.中段目标进动雷达特征提取[J].信号处理,2006,22(5):707--711.
[109]金文彬，刘永祥，任双桥，黎湘，庄钊文.锥体目标空间进动特性分析及其参数提取[J].宇航学报,2004,25(4):408--422.
[110]陈行勇，黎湘，郭桂蓉，姜斌.微进动弹道导弹目标雷达特征提取[J].电子与信息学报,2006,28(4):643--646.
[111] Maio A D, Farina A, Foglia G. Target fluctuation Models and Their Application toRadar Performance Prediction[J]. IEE Proceeding Radar Sonar Navigation,2004,151(5):261--269.
[112] Johnston S. Target Fluctuation Models for Radar System Design and PerformanceAnalysis: An Overwiew of Three Papers[J]. IEEE Transactions on Aerospace andElectronic Systems,1997,33(2):696--697.
[113]丁鹭飞，富录.雷达原理[M].西安:西安电子科技大学出版社,2002.
[114] Swerling P. Radar Probability of Detection for Some Additional Fluctuating Tar-get Cases[J]. IEEE Transactions on Aerospace and Electronic Systems,1997,22(2):698--709.
[115] Weinstock W. Target Cross Section Models for Radar System Analysis[D]. Penn-sylvania: University of Pennsylvania,1964.
[116] Meyer D P, Meyer H A. Radar Target Detection-Handbook of Theory and Prac-tice[M]. Alabama: Academic Press,1973.
[117] Ojha A K, Koch D B. Impact of Noise and Target Fluctuation on the performanceof Frank Polyphase Coded Radar Signals[C]The24th Southeastern Symposium onand The3rd Annual Symposium on Communications. Tennessee: System Theory,1992，第SSST/CSA92卷.
[118]赵宏钟，付强.基于循环平稳的复调频信号检测性能研究[J].电子学报,2004,32(6):942--945.
[119] Rutten M G, Gordon N J, Maskell S. Recursive Track-before-detect with Tar-get Amplitude Fluctuations[J]. IEE Processing on Radar Sonar Navigation,2005,152(5):345--352.
[120] Cumming I G, Wong F H. Digital Processing of Synthetic Aperture Radar Data--Algorithms and Implementation[M]. Canada: Artech House,2005.
[121] Martin J, Mulgrew B. Analysis of the theoretical radar return signal form air-craftpropeller blades[C]Record of the IEEE1990International Radar Conference.London, UK: IEEE,1990.
[122] MaioA,A.Farina, G.Foglia. NewTargetFluctuationModelsandTheirExperimen-tal Validation[J]. IEEE Transactions on Aerospace and Electronic Systems,1997,33(2):696--697.
[123] Skolnik M L. Radar Handbook,Third Edition[M]. USA: McGraw Hill Company,2008.
[124] Swami A. Cramer-Rao Bounds for Deterministic Signals in Additive and Multi-plicative Noise[J]. Signal Processing,1996,53(2):231--244.
[125] Ghogho M, Nandi A K, Swami A. Cramer-Rao Bounds and Maximum LikelihoodEstimation for Random Amplitude Phase-Modulated Signals[J]. IEEE Transactionon Signal Processing,1999,47(11):2905--2915.
[126] CurryG. RadarSystemPerformanceModeling[M]. BostonLondon: ArtechHouse,2005.
[127] Kay S M. Fundamentals of Statistical Signal Processing: Estimation Theory[M].New Jersey: Prentice Hall PTR,1993.
[128] Swerling P. Probability of Detection for Fluctuating Targets[J]. IRE Transactionson Information Theory,1960,6(2):269--308.
[129] CohenL. Time-frequencyAnalysis:TheoryandApplications[M]. NewYork,USA:PRENTICE HALL,1998.
[130] Baraniuk R G, Jones D L. A Signal-dependent Time-frequency Representation:Optimal Kernel Design[J]. IEEE Trans. on Signal Processing,1993,41(4):1589--16002.
[131] Baraniuk R G, Jones D L. A Signal-dependent Time-frequency Representation:Fast Algorithm for Optimal Kernal Design[J]. IEEE Trans. on Signal Processing,1994,42(1):134--146.
[132] Ouyang X, Amin M. Short-time Fourier Transform Reveiver for Nonstationary In-terference Excision in Direct Sequence Spread Spectrum Communication[J]. IEEETrans. on Signal Processing,2001,49(4):851--863.
[133] Durak L, Arikan O. Short-time Fourier Transform: Two Fundamental Propertiesand an Optimal Implementation[J]. IEEE Transactions on Signal Processing,2003,51(5):1231--1242.
[134] Nelson D. Signal Reconstruction from Concentrated STFT Peaks[C]IEEE Confer-ence on Acoustist Speech and Signal Processing. Philadelphia: IEEE,2005.
[135] Umapathy K, Krishnan S. Time-Width Versus Frequency Band Mapping of EnergyDistributions[J]. IEEE Transactions on Signal Processing,2007,55(3):978--989.
[136] Jones L D, Parks T W. A high resolution data-adaptive time-frequency represen-tation[J]. IEEE Transactions on Acoustics, Speech and Signal Processing,1990,38(12):2127--2135.
[137] Gonzalez R C, Woods R E, Eddins S L. Digital Image Processing (Second Edi-tion)[M]. Tennessee, USA: Prentice Hall,2002.
[138] Gonzalez R C, Woods R E. Digital Image Processing[M]. Beijing, China: Publish-ing House of Electronics Industry,2002.
[139]张光义，王德纯.空间探测相控阵雷达[M]. First.北京:科学出版社,2001.
[140] B. Z, N.K. B. Multi-target Tracking in Clutter: Fast Algorithms for Data Associa-tion[J]. IEEE Trans. on Aerospace and Electronic Systems,1993,29(2):352--363.
[141] Younghun J, Sunmog H. Modeling and Parameter Optimization of Agile BeamRadar Tracking[J]. IEEE Trans. on Aerospace and Electronic Systems,2003,39(1):12--33.
[142]刘兆磊，徐振来，张光义.基于多驻留测量的相控阵雷达目标跟踪算法[J].系统工程与电子技术,2006,28(3):376--379.
[143]孟建.分段采样信号的相位关联技术[J].系统工程与电子技术,2004,26(12):1784--1797.
[144]杜小勇.稀疏成份分析及在雷达成像处理中的应用[D].湖南长沙:国防科学技术大学,2005.
[145] M. V, P. M, T. B. Sampling Signals with Finite Rate of Innovation[J]. IEEE Trans.on Signal Processing,2002,50(6):1417--1428.
[146]刘吉英.压缩感知理论及在成像中的应用[D].湖南长沙:国防科学技术大学,2010.
[147] Muthukrishnan S. Data Streams: Algorithms and Applications[M]. Boston: NowPunlishers,2005.
[148] Blu T, Dragotti P, Vetterli M, et al. Sparse Sampling of Signal Innovations[J]. IEEESignal Processing Magazine,2008.
[149] G. M S, F. Z Z. Matching Pursuits with Time-frequency Dictionaries[J]. IEEETrans. on Signal Processing,1993,41(12):3397--3415.
[150] TroppJ. ComputaionalMethodsforSparseSolutionofLinearInverseProblems[C].Latfayette College: Proceedings of the IEEE,2009.
[151] ChenSS,DonohoDL,SaundersMA. AtomicDecompositionbyBasicPursuit[J].SIAM Journal on Scientific Computing,1998,20(1):33--61.
[152] McClure M R, Carin L. Matching Pursuits with a Wave-based Dictionary[J]. IEEETrans. on Signal Processing,1997,45(12):2912--2927.
[153] Tropp J A, Gilber A C. Signal Recovery From Random Measurements Via Or-thogonal Matching Pursuit[J]. IEEE Transactions on Information Theory,2007,53(12):4655--4666.
[154] Needell D, Vershynin R. Uniform Uncertainty Principle and Signal RecoveryVia Regularized Orthogonal Matching Pursuit[J]. Found. Comput Math.,2008,9(3):95--103.
[155] Needell D, Tropp J A. CoSaMP: Iterative Signal Recovery From Incomplete andInaccurate Samples[J]. Applied and Computational Harmonic Analysis,2009,26(1):301--321.
[156] Elad M, Bruckstein A. A Generalized Uncertainty Principle and Sparse Represen-tation in Pairs of Bases[J]. IEEE Trans. on Information Theory,2002,48(9):2558--2567.
[157] Gribonval R, Nielsen M. Sparse Representations in Unions of Bases[J]. IEEETrans. on Information Theory,2003,49(12):3320--3325.
[158] A Matlab Toolbox for Optimization Over Symmetric Cones[M].[S.l.]:[s.n.]. http://www.unimaas.nl/~sturm/papers/guide.ps.gz.
[159] Mathematical Programming System[M].[S.l.]:[s.n.]. http://www.mosek.com.
[160] l1-magic[M].[S.l.]:[s.n.]. http://www.acm.caltech.edu/l1magic/.
[161] SparseLab Software[M].[S.l.]:[s.n.]. http://sparselab.stanford.edu.
[162] PDCO:Primal-DualInteriorMethodforConvexObjectives[M].[S.l.]:[s.n.]. http://www.stanford.edu/group/SOL/software/pdco.html.
[163] Wright S, Nowak R, Figueiredo M. Sparse Reconstruction by Separable Approxi-mation[J]. IEEE Trans. on Signal Processing,2009,57.
[164] R. T. Regression Shrinkage and Selection Via the LASSO[J]. J.R.Statist. Soc. B,1996,58(1):267--288.
[165] R. C. Exact Reconstruction of Sparse Signals via Nonconvex Minimization[J].IEEE Signal Processing Letters,2007,14(10):707--710.
[166] E.J. C, M.B. W, S.P. B. Enhancing Sparsity by Reweighted l1Minimization[J]. J.Fourier Anal. Appl.,2008,14(5):877--905.
[167] E.G. L, Y. S. Linear Regression with a Sparse Parameter Vector[J]. IEEE Trans.on Signal Processing,2007,55(2):451--460.
[168] D.W,B.R. SparseBayesianLearningforBasisSelection[J]. IEEETrans.onSignalProcessing,2004,52(8):2153--2164.
[169] S. J, W. X, B. H, et al. Efficient Compressed Sensing Using Optimized ExpanderGraphs[J]. IEEE Trans. on Information Theory,2009,55(2):4299--4308.
[170] D.L. D, A. M, A. M. Message-passing Algorithms for Compressed Sensing[J].Proc. Natl. Acad. Sci.,2009,106(45):18914--18919.
[171] CandesE,TaoT. DecodingbyLinearProgramming[J]. IEEETrans.onInformationTheory,2006,51.
[172] Candes E, T.Tao. Near-optimal Signal Recovery From Random Projections:Universal Encoding Strategies?[J]. IEEE Trans. on Information Theory,2006,52(12):5406--5425.
[173] Baraniuk R G. Compressive Sensing[C].[S.l.]: Proceedings of the IEEE,2009.
[174] BaraniukR,DavenportM,DevoreR,等. ASimpleProofoftheRestrictedIsometryProperty for Random Matrics[J]. Constructive Approximation,2008,28(3):253--263.
[175] Zhang Y. A Simple Proof for Recoverability of l1-minimization: Go Over orUnder[C]Rice University CAAM Technical Report. Rice: Rice University,2005，第TR05-09卷.
[176] Cohen A, Dahmen W, DeVore R. Compressed Sensing and Best K-term Approxi-mation[J]. Journal of the American Mathematical Society,2009,22(1):211--231.
[177] Tropp J. Greed is good: Algorithmic Results for Sparse Approximation[J]. IEEETrans. on Information Theory,2006,50.
[178] KimKT,KimHT. Two-dimensionalScatteringCenterExtractionBasedonMulti-ple Elastic Modules Network[J]. IEEE Transactions on Antennas and Propagation,2003,51(4):848--861.
[179] Li K, Jiang W, Liu Y. Feature Extraction of Cone with Precession Based on Micro-Doppler[C]. Guilin, China: IET,2009.
[180] Swiger J M. Resolution Limits of Ultra Wideband Synthetic Aperture Radar Usinga Rectangular Aperture for FFT Processing[J]. IEEE Transactions on Aerospaceand Electronic Systems,1994,30(3):935--938.
[181] Elad M. Optimized Projections for Compressed Sensing[J]. IEEE Trans. on SignalProcessing,2007,12(1):5695--5702.
[182] Duarte-CarvajalinoJM,SapiroG. LearningtoSenseSparseSignals: SimultaneousSensing Matrix and Sparsifying Dictionary Optimization[J]. IEEE Trans. on ImageProcessing,2009,18(7):1395--1408.
[183] Ghogho M, Swami A, Nandi A. Nonlinear Least Squares Estimation for Har-monics in Multiplicative and Additive Noise[J]. Elsevier Signal Processing,1999,78(1):43--60.
[184] Agni-strategic Ballistic Missile[M].[S.l.]:[s.n.]. http://www.bharat-rakshak.com/land-forces/Equipment/Others/379-Agni-IRBM-(Page-1).html.