【作者】 李康乐；

【导师】 庄钊文； 黎湘；

【作者基本信息】 国防科学技术大学 ， 信息与通信工程， 2010， 博士

【摘要】 目标或目标的组成部分除主体平动之外的振动、转动等小幅运动称为微动,目标微动反映了其精细特征,具有重要的军事价值,在目标探测与识别领域受到广泛关注。本文系统研究了微动目标雷达回波的调制效应,在此基础上提出了微多普勒特征提取的方法,并深入研究了非参数化和基于模型的两大类微动参数估计方法。第一章阐述了课题研究背景及意义,归纳了微动的研究现状,从微动目标雷达回波建模、微多普勒分离及特征提取、微动目标成像、基于微多普勒特征的目标识别等方面分析并总结了该领域研究目前采取的主要技术途径及存在的问题,介绍了本文主要研究工作。第二章系统研究了微动目标雷达回波调制效应。在分析微动目标姿态变化引起的散射强度变化规律基础上,建立了多成分调幅-调频形式的进动目标雷达回波调制模型,研究了进动目标微多普勒和多普勒谱的调制特性,推导了其与进动参数的定量关系。针对LFM和SF两种典型宽带信号,系统建立了不同雷达参数和微动参数条件下的微动目标一维距离像调制模型,分析了其移位、展宽等调制特性,对微动参数估计和微动目标成像的研究具有重要意义。通过系列暗室测量实验分析了目标特性和雷达信号特性两方面因素对雷达目标微动特性测量的影响。第三章研究了目标微多普勒特征提取与进动参数估计方法。针对微动目标回波信号多分量非线性调频的特点,研究了高阶时频分布在微多普勒特征提取中的应用并分析了其性能,该方法具备高时频分辨力、低交叉项、大动态范围的分析性能。针对弹道目标回波微多普勒提取的问题,提出了基于瞬时频率多项式模型的目标平动估计方法,从而实现了微动与平动多普勒谱的分离。针对微动目标回波的循环平稳特性,建立了微动目标回波循环谱密度统计量的模型,提出了基于循环谱密度的微动周期估计方法,该方法具有估计精度高、抗噪性能强的特点。分析了进动目标微多普勒谱图的调制特性以及高阶时频分布估计微多普勒瞬时频率的偏差规律,在此基础上提出了改进的逆约旦变换估计进动角方法,提高了进动角的估计精度。第四章研究了基于模型的目标微动参数估计方法。针对微动目标雷达回波具有稀疏性的特点,建立了基于稀疏表示的微动目标参数估计模型,设计了微动目标的原子模型,并分析了字典的相干性。针对微动目标字典相干性强的问题,提出了基于线性变换的字典优化设计方法,该方法在不影响稀疏解性质的前提下,有效减小了字典的相干性。将字典线性变换与稀疏求解算法相结合,设计了基于稀疏表示的目标微动参数估计算法流程,获得了优良的估计性能。针对进动目标回波信号调幅-调频的特点,建立了进动目标回波的时变自回归(TVAR)表示模型,提出了基于TVAR模型的目标微动参数估计方法。第五章总结了论文的研究工作和主要创新点,指出需要进一步研究的问题。更多还原

【Abstract】 The term”micro-motion”is defined as the mechanical vibration or rotation of a target or its components in addition to its bulk translation. The micro-motion status of a target can well reflect its sophisticated features. Therefore, it is of important value in military field, and draws great attentions to the researchers from the areas of target detection and recognition. In this dissertation, we keep our focus and do intensive research works on the topic of radar signature extraction from targets with micro-motions based on the modulation effects of the radar echo on this specific kind of targets.We introduce the background and significance of this research topic as well as the related works in Chapter 1. The state of the art is summarized under four aspects: the radar echo modeling of targets with micro-motions; the separation and feature extraction of micro-Doppler; the radar imaging of targets with micro-motions; and the target recognition based on micro-Doppler. We analyze the basic methodologies and techniques commonly used in this area, and point out their main problems. The major scientific contributions of this dissertation are summed up at the end of this chapter as well.In Chapter 2, we analyze the modulation effects of micro-motions on the radar echo of targets systematically. The modulation effects and characteristics are investigated according to micro-motions, the scattering structure of the target and radar waveforms. The radar echo model of targets with precession is established. The micro-Doppler and Doppler spectrum of targets with precession are deduced and analyzed. Under the two different conditions of the typical wideband waveform– LFM (Linear Frequency Modulation) signal and SF (Stepped Frequency) signal, we do deduction and analysis on the modulation regularities of the HRRP (high resolution range profile) with different parameters of radar waveforms and micro-motions respectively. The influences of target characteristics and radar waveforms on micro-Doppler are analyzed, including micro-motion pattern, scattering structure, radar frequency, instantaneous bandwidth, Doppler resolution and coherence of echos. The conclusion is verified by a series of experiments conducted both on the simulated and measured data.The methodology of analysis and extraction of micro-Doppler signatures are deeply studied in Chapter 3. We firstly analyze the performances of the different typical time-frequency distributions in micro-Doppler extraction. As the ballistic targets have both the high-velocity bulk translation and micro-motion characteristics, we propose an approach to estimate the bulk velocity based on a polynomial model of instantaneous frequency. With the support of this approach, the micro-Doppler and Doppler spectrum of the bulk motion can be separated. Then, aiming at the cyclostationary characteristic of the radar echo of targets with micro-motions, an estimation method of the micro-motion cycle based on CSD (Cyclic Spectral Denstiy) is proposed, and its performance is discussed afterwards. According to the characteristics of micro-Doppler on time-frequency distribution images, we estimate the precession angle by utilizing the inverse Radon transformation. While analyzing the bias of the estimation, we propose a method for correcting that of the precession angle.We elaborate the super-resolution estimation of micro-motion parameters in Chapter 4. Since the radar echo of targets with micro-motions is sparse, we establish a model based on sparse representation for estimating the micro-motion parameters, design the atom model of targets with micro-motions, and analyze the mutual coherence of the dictionary. For solving the problem of strong mutual coherence of the dictionary, we optimize the dictionary design by applying the theory of linear transformation. The mutual coherence of the dictionary can be effectively reduced with the solution’s sparsity property held. In addition, we develop a sparse-representation-based algorithm for the micro-motion parameters estimation by integrating the dictionary transformation with the sparse solution solvers. The performance of the algorithm is verified as being acceptable by experiments. The radar echo of targets with micro-motions belongs to multi-component AM-FM signal models. Taking this characteristic into account, we propose a time-varying autoregressive (TVAR) representation model of the radar echo of targets with micro-motions. The methods of solving the TVAR model’s parameters are discussed, and the micro-motion parameters are estimated.The research work and main innovative contributions of this dissertation are concluded in the final chapter. We not only outlook the work can be done in the next steps, but point out the potential problems and difficulties.更多还原