摘要
摘要
雷达自动目标识别(Radar Automatic Target Recognition, RATR)能通过雷达回波信号确定目标属性，能全天时、全天候地获取目标类别、型号等信息，在众多领域被广泛使用。当雷达照射运动目标时，目标除质心平动外，其重要部件往往还存在旋转、振动等复杂的微运动形式。这些微运动将会对目标的回波信号产生频率调制，致使多普勒谱边缘出现边带，此即为微多普勒效应。由于目标具有的复杂运动形式将会对RATR性能造成严重的影响，RATR系统迫切需要进一步提升目标运动状态精细描述的能力，因此运动目标的微多普勒特征分析成为了一种最为有效的途径。为此，本文围绕微动目标微多普勒特征的提取和分析等问题展开研究和讨论，主要工作包含以下几个方面： 1. 以运动目标电磁散射特性为切入点，建立运动目标雷达回波模型，并进一步得到运动目标的时变多普勒理论模型。利用振动与旋转两种常见微运动与雷达平台间的几何关系，通过数学建模的方式建立微多普勒频率的理论表达式，并分析微动参数对微多普勒频率的影响，建立了目标微运动状态与其微多普勒特征的对应关系。
2. 分析了线性时频表示、双线性时频分布、自适应时频分布和小波分解类时频分析四大类主要的时频分析方法并简单介绍了其在微多普勒特征提取中的应用。通过仿真实验定性地分析各类时频方法的优缺点， 同时还选取均方根误差(Root Mean Square Error, RMSE)定量地评价各类时频算法的性能。阿尔法氨基酸
3. 利用时频分析技术，针对海面漂浮浮标、四旋翼无人机叶片和雷达天线三类典型目标的复杂微运动所引起的微多普勒特征进行分析。从非线性动力学建模入手，利用散射点模型建立微动目标后向散射RCS模型，从而建立其微动目标雷达回波信号模型，最后应用时频分析技术分析了这三类不同微动目标的微多普勒特征。
关键词：电磁散射，微动，微多普勒效应，时频分析技术
ABSTRACT
Radar Automatic Target Recognition (RATR) systems have ability to recognize the target attributes from the radar echo in all-time and all-weather conditions, and therefore widely applied in the military and civilian. Illuminated by radar systems, the moving target or its components always exists some type of complex micro motion forms, such as rotation and vibration. This type of micro motion generates the different Doppler modulations at different times, and results to typically non-stationary characteristics in radar echoes of the moving target, which is named micro-Doppler effects. With the development of RATR systems, there is an urgent demand for improving the ability to accurately describe the target states, which could seriously decrease the performance of RATR system. Theref
ore, the micro-Doppler characteristics analysis can be considered as an effective method to characterize the local features of the target with micro motion. This paper revolves the problems in micro-Doppler characteristics extraction and analysis and is major in the following aspects.
The fundamental concepts of micro-motion and micro-Doppler effect of the target are discussed. Herein, the electromagnetic scattering characteristics of micro-moving targets are considered as the starting point, and then the radar echoes model of moving target is established. Furthermore, the theoretical model of the Doppler modulations of the moving target is obtained. According to the geometrical relationship between the micro-moving target and the radar platform, the theoretical expressions of micro-Doppler frequency induced by the basic micro-motions, such as rotation and vibration, derive by mathematical modeling. Finally, the influence of the micro-motion parameters on the micro-Doppler frequency is analyzed in detail, and the relationship between micro-Doppler features and the movement states of targets is concluded.
A series of efficient features are extracted from micro-Doppler signal by using time-frequency analysis techniques. This paper reviews a sample of representative time-frequency analysis algorithms. Their performance is studied from a qualitative and quantitative point of view. For simplicity, we considered the root mean-squared error (RMSE) as measures of performance in the q
稀土永磁uantitative trade-off studies. Finally, the time-frequency features extraction from micro-Doppler signal of the rotational radar
西安电子科技大学硕士学位论文
antenna is discussed.
The micro-Doppler characteristics of the buoy on the sea-surface, the unmanned aerial vehicle rotor blades, and the parabolic reflector antenna are systematically analyzed by using the time-frequency analysis techniques. According to the modeling of the non-linear dynamics, the spatial electromagnetic scattering distribution of the three classical types of micro-moving targets can be calculated by method of equivalent edge currents (MEC). With adoption of the time-frequency analysis techniques, favorable micro-Doppler characteristics of them are obtained.
Keywords:electromagnetic scattering, micro-motion, micro-Doppler effect, time-frequency analysis techniques.
插图索引
插图索引
图1.1RATR处理流程图 (1)
图2.1 微动目标回波信号多普勒谱 (7)
图2.2 等效线电流和线磁流示意图 (9)
大叶黄杨白粉病图2.3 面元间劈结构示意图 (9)
图2.4 导体立方体模型示意图 (10)
图2.5 导体立方体后向散射结果 (10)
图2.6 复杂飞机目标模型 (11)
图2.7 飞机目标后向散射随方位角的变化情况 (11)
图2.8 远场运动目标几何关系 (12)
图2.9 目标六自由度运动示意图 (12)
图2.10 振动目标几何模型 (16)
高中语文教学大纲图2.11 电磁波载频对振动目标微多普勒频率的影响 (17)
图2.12 振动幅度对微多普勒频率的影响 (17)
图2.13 振动频率对微多普勒频率的影响 (18)
图2.14 旋转目标的几何模型 (18)
图2.15 旋转角速度对微多普勒频率的影响 (20)
图2.16 旋转半径对微多普勒频率的影响 (20)
图3.1 微动目标微多普勒效应时间-频率变化关系 (23)
图3.2 FrFT变换域原理图 (32)
图3.3 固定频率的调频信号 (33)
图3.4 固定频率的调频信号参考时频分布 (34)
图3.5 固定频率的调频信号STFT时频图 (34)
图3.6 Kaiser-Bessel窗宽对STFT的影响 (35)
图3.7 固定频率的调频信号CWT时频图 (35)
图3.8 固定频率的调频信号二次型时频分布 (36)
图3.9 固定频率的调频信号FrFT时频图 (37)
图3.10 线性调频信号 (39)
图3.11 线性调频信号参考时频分布 (39)
图3.12 线性调频信号的时频分布图 (40)
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西安电子科技大学硕士学位论文
图3.13 非线性调频信号 (41)
白世峰图3.14 非线性调频信号的时频分布图 (42)
图3.15 非线性调频信号的AOK分布 (42)
图3.16 非线性调频信号的FrFT分布 (42)
图4.1 海面浮标模型示意图 (46)
图4.2 浮标小球的三维转动角度变化曲线 (47)
图4.3 浮标小球横滚摆动角度 (48)
图4.4 浮标小球横滚转动雷达回波信号 (50)
图4.5 浮标小球横滚转动回波信号多普勒谱 (51)
图4.6 浮标小球俯仰转动雷达回波信号 (51)
拜金一族图4.7 浮标小球俯仰转动回波信号多普勒谱 (51)
图4.8 浮标小球偏航转动雷达回波信号 (52)
图4.9 浮标小球偏航转动回波信号多普勒谱 (52)
图4.10 浮标小球横滚转动微多普勒特征 (53)
图4.11 浮标小球俯仰转动微多普勒特征 (53)
图4.12 浮标小球偏航转动微多普勒特征 (53)
图4.13 UA V微运动几何模型示意图 (54)
图4.14 四旋翼UA V结构示意图 (55)
图4.15 旋翼与雷达平台几何关系示意图 (56)
图4.16 UA V旋翼时域和频域特征 (57)
图4.17 频谱混叠现象 (57)
图4.18 UA V旋翼微多普勒特征 (58)
图4.19 欠采样信号的微多普勒特征 (59)
图4.20 UA V悬停微多普勒特征 (59)
图4.21 UA V俯仰转动的微多普勒特征 (60)
图4.22 UA V横滚转动的微多普勒特征 (60)
图4.23 UA V偏航转动的微多普勒特征 (61)
图4.24 抛物面反射器天线的几何模型 (61)
图4.25 抛物面反射器天线的三角面元剖分结果 (62)
图4.26 抛物面反射器天线后向散射特性 (63)
图4.27 雷达回波I通道和Q通道数据 (63)
图4.28 抛物面反射器天线的微多普勒特征 (64)
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