【作者】 刘丽华；

【导师】 胡卫东；

【作者基本信息】 国防科学技术大学 ， 信息与通信工程， 2012， 博士

【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。更多还原

【Abstract】 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.更多还原