弹道目标的微多普勒特征提取与重构方法研究
发布时间：2018-08-01 10:21
【摘要】：目标与雷达之间的相对微运动(如振动、旋转、翻滚和进动等)会对回波信号进行调制,产生微多普勒效应。对微动目标的微多普勒进行提取重构并加以测量可获得目标的微动参数和结构参数,基于此的目标检测识别技术被认为是雷达目标精确检测识别领域中有巨大发展前景的研究方向之一。针对弹道目标微多普勒特征提取与重构方法的主要研究成果如下:1.分析了微动目标的微多普勒调制效应。针对窄带和宽带两种信号形式,分别建立了目标进动的雷达回波模型,研究了进动目标微多普勒的调制特性,推导了微多普勒与进动参数和目标结构参数的定量表达式,最后对比分析了微多普勒特征提取常用的时频分析工具,对微动目标特征的提取重构和参数估计具有重要的理论研究意义。2.在窄带信号情况下提出了基于短时迭代自适应-逆Radon变换(Short Time Iterative Adaptive Approach-Inverse Radon Transform,STIAA-IRT)的微多普勒特征提取与参数估计方法。首先针对短观测时间常用时频分析方法分辨力不足,难以区分频率交叠严重且成分接近分量的问题,采用基于短时迭代自适应(Short Time Iterative Adaptive Approach,STIAA)的时频分析方法对目标散射点模型进行微多普勒特性提取。然后针对多分量微多普勒信号难以一一提取瞬时频率以及信噪比较低的问题,利用逆Radon变换(Inverse Radon Transform,IRT)分离重构不同散射点的微多普勒分量。该方法在低信噪比情况下能获得多分量信号的完整微多普勒信息,为低信噪比、邻近时频分布情况下的微动特征分离重构和参数估计提供了有效途径,最后利用仿真实验验证了所提方法具有优于短时傅里叶变换和S方法的分辨能力和重构性能。3.在宽带信号情况下进一步提出了基于逆Radon变换(IRT)的参数域微多普勒聚焦融合估计方法。首先针对宽带信号微动跨越距离单元的问题,采用子带划分的方法,将各子带的窄带信号分别利用STIAA时频分析方法得到微多普勒时频谱。然后针对各子带间存在多普勒色散的问题,研究了对时频图进行IRT后的参数空间实施变换以实现不同子带的微多普勒聚焦融合的方法。该方法在低信噪比情况下能获得宽带目标各散射点的高分辨微多普勒信号,提高了参数的估计精度,最后利用仿真实验验证了所提方法的有效性。
[Abstract]:The relative micro-motion between target and radar (such as vibration, rotation, roll and precession) will modulate the echo signal and produce micro-Doppler effect. The micro-Doppler of the fretting target is extracted and reconstructed, and the fretting parameters and structure parameters of the target are obtained. The technology of target detection and recognition based on this is considered to be one of the promising research directions in the field of accurate detection and recognition of radar targets. The main research results of micro-Doppler feature extraction and reconstruction for ballistic targets are as follows: 1. The micro-Doppler modulation effect of fretting target is analyzed. The radar echo models of target precession are established for narrowband and wideband signals respectively. The modulation characteristics of micro-Doppler of precession target are studied. The quantitative expressions of micro-Doppler parameters, precession parameters and target structure parameters are derived. Finally, the time-frequency analysis tools commonly used in micro-Doppler feature extraction are compared and analyzed, which has important theoretical significance for feature extraction and parameter estimation of fretting target. A method for feature extraction and parameter estimation of microDoppler based on (Short Time Iterative Adaptive Approach-Inverse Radon transform STIAA-IRT is proposed for narrowband signals. First of all, due to the lack of resolution of time-frequency analysis methods commonly used in short observation time, it is difficult to distinguish the overlapping frequencies and the components close to the components. The time-frequency analysis method based on short-time iterative adaptive (Short Time Iterative Adaptive Approach-STIAA) is used to extract the micro-Doppler characteristics of the scattering point model of the target. Then, it is difficult to extract the instantaneous frequency and low SNR from multi-component microDoppler signals. The inverse Radon transform (Inverse Radon transform is used to separate and reconstruct the micro-Doppler components of different scattering points. This method can obtain the complete micro-Doppler information of multi-component signal under low SNR, which provides an effective way for fretting feature separation reconstruction and parameter estimation under low signal-to-noise ratio and adjacent time-frequency distribution. Finally, the simulation results show that the proposed method has better resolution and reconstruction performance than the STFT and S-method. In the case of wideband signal, a parameter domain micro-Doppler focusing fusion estimation method based on inverse Radon transform (IRT) is proposed. Firstly, aiming at the problem of wideband signal fretting span distance unit, the sub-band division method is used to obtain the micro-Doppler time-frequency spectrum by using the STIAA time-frequency analysis method for each sub-band narrowband signal. Then, aiming at the problem of Doppler dispersion among the sub-bands, the method of implementing the parameter space transformation of time-frequency map after IRT to realize the micro-Doppler focusing fusion of different sub-bands is studied. In the case of low SNR, the proposed method can obtain high-resolution micro-Doppler signals from each scattering point of a wideband target and improve the precision of parameter estimation. Finally, the effectiveness of the proposed method is verified by simulation experiments.
【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN957.51
本文编号：2157261
[Abstract]:The relative micro-motion between target and radar (such as vibration, rotation, roll and precession) will modulate the echo signal and produce micro-Doppler effect. The micro-Doppler of the fretting target is extracted and reconstructed, and the fretting parameters and structure parameters of the target are obtained. The technology of target detection and recognition based on this is considered to be one of the promising research directions in the field of accurate detection and recognition of radar targets. The main research results of micro-Doppler feature extraction and reconstruction for ballistic targets are as follows: 1. The micro-Doppler modulation effect of fretting target is analyzed. The radar echo models of target precession are established for narrowband and wideband signals respectively. The modulation characteristics of micro-Doppler of precession target are studied. The quantitative expressions of micro-Doppler parameters, precession parameters and target structure parameters are derived. Finally, the time-frequency analysis tools commonly used in micro-Doppler feature extraction are compared and analyzed, which has important theoretical significance for feature extraction and parameter estimation of fretting target. A method for feature extraction and parameter estimation of microDoppler based on (Short Time Iterative Adaptive Approach-Inverse Radon transform STIAA-IRT is proposed for narrowband signals. First of all, due to the lack of resolution of time-frequency analysis methods commonly used in short observation time, it is difficult to distinguish the overlapping frequencies and the components close to the components. The time-frequency analysis method based on short-time iterative adaptive (Short Time Iterative Adaptive Approach-STIAA) is used to extract the micro-Doppler characteristics of the scattering point model of the target. Then, it is difficult to extract the instantaneous frequency and low SNR from multi-component microDoppler signals. The inverse Radon transform (Inverse Radon transform is used to separate and reconstruct the micro-Doppler components of different scattering points. This method can obtain the complete micro-Doppler information of multi-component signal under low SNR, which provides an effective way for fretting feature separation reconstruction and parameter estimation under low signal-to-noise ratio and adjacent time-frequency distribution. Finally, the simulation results show that the proposed method has better resolution and reconstruction performance than the STFT and S-method. In the case of wideband signal, a parameter domain micro-Doppler focusing fusion estimation method based on inverse Radon transform (IRT) is proposed. Firstly, aiming at the problem of wideband signal fretting span distance unit, the sub-band division method is used to obtain the micro-Doppler time-frequency spectrum by using the STIAA time-frequency analysis method for each sub-band narrowband signal. Then, aiming at the problem of Doppler dispersion among the sub-bands, the method of implementing the parameter space transformation of time-frequency map after IRT to realize the micro-Doppler focusing fusion of different sub-bands is studied. In the case of low SNR, the proposed method can obtain high-resolution micro-Doppler signals from each scattering point of a wideband target and improve the precision of parameter estimation. Finally, the effectiveness of the proposed method is verified by simulation experiments.
【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN957.51
【参考文献】
相关期刊论文 前1条
1 高红卫;谢良贵;文树梁;匡勇;;微多普勒的一些工程问题研究[J];系统工程与电子技术;2008年11期
，本文编号：2157261
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