复杂雷达回波特征提取及信号检测
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摘要
以智能化为核心内涵的下一代雷达技术已在科技进步和国防应用彰显其重要性。目前感知雷达、知识辅助的自适应雷达、基于知识的雷达信号处理以及空时自适应信号处理等都是国内外研究的热点，然而在上述研究范畴中有一个共同的关键问题，那就是对复杂环境和目标的雷达回波信号中包含的各种成分进行分析、理解、提取，进而实现微弱目标检测。
通过对环境杂波动态特性的分析，研究适合于复杂雷达回波的特征提取方法，能够充分利用回波中蕴含的环境参数信息、结构属性信息，实现低信杂比条件下的自适应信号检测。本文立足于复杂数据分析和雷达信号处理的最新研究成果，从复杂雷达回波信号的特性分析入手，讨论了宽带情形下和高阶域上分析多分量非平稳信号的具体方法，以及雷达回波中进行微多普勒特征提取和拓扑结构特征提取的技术途径，最终通过海杂波中的微弱信号检测来检验方法的可行性与实际效果，并形成系统分析复杂雷达回波信号的内容框架。
主要研究内容概括如下：
1、研究复杂雷达回波信号特性分析方法。首先对回波序列中的复杂性和不确定性进行了定量分析，然后介绍了本文后续章节进行实验分析的实测数据样本，并给出了一种基于变尺度相关分析的数据预处理方法。讨论了复杂雷达回波的序列分析方法，最后在联合域上开展雷达回波信号的研究，讨论了宽带情形下和高阶域上分析多分量非平稳信号的具体方法。提出了对局域模糊和全域相关的一体化分析方法，这是对联合域能量分布一种结构化表示。
2、研究复杂雷达回波特征提取的几种方法，包括：基于微多普勒特征的海面弱目标特征提取方法；结合拓扑分析，提出了基于保持同调的流形拓扑特征提取方法；基于有限时间Lyapunov指数，得到更进一步的流形结构特征描述。最后，利用这些特征提取的结果确定重构参数，实现基于联合域能量分布的相空间重构。
3、提出了两种用于复杂雷达回波的信号检测方法。首先应用基于拓扑结构特征的检测方法，为在复杂多变的高维数据集上获取包含信号数目及特性的拓扑不变量，进而实现杂波环境下微弱信号检测；其次在雷达回波多维特征空间上，利用多维参考滑窗在各个轴向上都进行局部化和单元化，解决低信杂比条件下局部海域同时检测多个小目标的问题。
综上，本文以复杂环境与目标特性分析和为背景，针对雷达回波信号的特性分析、特征提取和微弱目标检测等关键技术，展开了深入的研究和探索，取得了一些有价值的研究成果。
“Intelligent” technique considered to be a core point for the next generation radarsystems has played a more and more important role in technology progress and defenseapplications. For radar signal processing, how to apply characteristic analysis andextraction followed by target detection for weak targets in the complex radar returnsignals is a desirable investigation topic with both theoretic and real values. By learningthe dynamic clutter environments characteristics and analyzing the radar return signals,a higher signal-to-clutter ratio and a lower false rate can be achieved with effectivecharacteristic extraction methods and proper targets detection approaches.
This dissertation is based on the existing work on complex data analysis and radarsignal processing and focuses on the investigation of characteristic extractionapproaches for the complex radar signals. Then the measured data are used to illustratethe effectiveness of the proposed approaches for weak targets detection. In addition, thepaper also describes the framework for the system analysis of the complex radar signals.The main contents are listed as follows:
1) Considers the characteristics analysis methods of the complex radar signals. Itfirst takes the quantificational analysis to the complexity and uncertainty of the signals,then introduce the measured data which are used by following contents. A pretreatmentmethod based on Scaled Correlation Analysis is proposed. Discussion on the analysis ofcomplex radar echo series is finally extended to joint-domain, and the concrete methodsof multi-component non-stationary signal are investigated under both broadband andhigh-order circumstances.
2) Several feature extraction methods are investigated in complex radar echo.based on topological pattern discovery. This approach reconstructs the phase space ofcomplex radar signals by extracting the topological structural features and analyzing thetopological invariants.
3) Two targets detection methods in the complex radar signals is proposed,including weak targets detection based on micro-Doppler analysis, weak targetsdetection based on topological structural features, constant false alarm rate detectionbased on3D feature space of radar signal. Numerical results validate the performance ofthe proposed methods in very low SCR environments.
To sum up, based on investigation background of complex environment and target,the dissertation and presents some contribution for future works. Around the keyquestions of characteristic analysis, feature extraction and weak target detection, theresearch provide theoretic summary and real applications in radar signal processing.
通过对环境杂波动态特性的分析，研究适合于复杂雷达回波的特征提取方法，能够充分利用回波中蕴含的环境参数信息、结构属性信息，实现低信杂比条件下的自适应信号检测。本文立足于复杂数据分析和雷达信号处理的最新研究成果，从复杂雷达回波信号的特性分析入手，讨论了宽带情形下和高阶域上分析多分量非平稳信号的具体方法，以及雷达回波中进行微多普勒特征提取和拓扑结构特征提取的技术途径，最终通过海杂波中的微弱信号检测来检验方法的可行性与实际效果，并形成系统分析复杂雷达回波信号的内容框架。
主要研究内容概括如下：
1、研究复杂雷达回波信号特性分析方法。首先对回波序列中的复杂性和不确定性进行了定量分析，然后介绍了本文后续章节进行实验分析的实测数据样本，并给出了一种基于变尺度相关分析的数据预处理方法。讨论了复杂雷达回波的序列分析方法，最后在联合域上开展雷达回波信号的研究，讨论了宽带情形下和高阶域上分析多分量非平稳信号的具体方法。提出了对局域模糊和全域相关的一体化分析方法，这是对联合域能量分布一种结构化表示。
2、研究复杂雷达回波特征提取的几种方法，包括：基于微多普勒特征的海面弱目标特征提取方法；结合拓扑分析，提出了基于保持同调的流形拓扑特征提取方法；基于有限时间Lyapunov指数，得到更进一步的流形结构特征描述。最后，利用这些特征提取的结果确定重构参数，实现基于联合域能量分布的相空间重构。
3、提出了两种用于复杂雷达回波的信号检测方法。首先应用基于拓扑结构特征的检测方法，为在复杂多变的高维数据集上获取包含信号数目及特性的拓扑不变量，进而实现杂波环境下微弱信号检测；其次在雷达回波多维特征空间上，利用多维参考滑窗在各个轴向上都进行局部化和单元化，解决低信杂比条件下局部海域同时检测多个小目标的问题。
综上，本文以复杂环境与目标特性分析和为背景，针对雷达回波信号的特性分析、特征提取和微弱目标检测等关键技术，展开了深入的研究和探索，取得了一些有价值的研究成果。
“Intelligent” technique considered to be a core point for the next generation radarsystems has played a more and more important role in technology progress and defenseapplications. For radar signal processing, how to apply characteristic analysis andextraction followed by target detection for weak targets in the complex radar returnsignals is a desirable investigation topic with both theoretic and real values. By learningthe dynamic clutter environments characteristics and analyzing the radar return signals,a higher signal-to-clutter ratio and a lower false rate can be achieved with effectivecharacteristic extraction methods and proper targets detection approaches.
This dissertation is based on the existing work on complex data analysis and radarsignal processing and focuses on the investigation of characteristic extractionapproaches for the complex radar signals. Then the measured data are used to illustratethe effectiveness of the proposed approaches for weak targets detection. In addition, thepaper also describes the framework for the system analysis of the complex radar signals.The main contents are listed as follows:
1) Considers the characteristics analysis methods of the complex radar signals. Itfirst takes the quantificational analysis to the complexity and uncertainty of the signals,then introduce the measured data which are used by following contents. A pretreatmentmethod based on Scaled Correlation Analysis is proposed. Discussion on the analysis ofcomplex radar echo series is finally extended to joint-domain, and the concrete methodsof multi-component non-stationary signal are investigated under both broadband andhigh-order circumstances.
2) Several feature extraction methods are investigated in complex radar echo.based on topological pattern discovery. This approach reconstructs the phase space ofcomplex radar signals by extracting the topological structural features and analyzing thetopological invariants.
3) Two targets detection methods in the complex radar signals is proposed,including weak targets detection based on micro-Doppler analysis, weak targetsdetection based on topological structural features, constant false alarm rate detectionbased on3D feature space of radar signal. Numerical results validate the performance ofthe proposed methods in very low SCR environments.
To sum up, based on investigation background of complex environment and target,the dissertation and presents some contribution for future works. Around the keyquestions of characteristic analysis, feature extraction and weak target detection, theresearch provide theoretic summary and real applications in radar signal processing.
引文
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