基于盲源分离的MIMO雷达侦察与识别
发布时间：2018-07-23 07:51
【摘要】：多输入多输出(Multiple Input Multiple Output,MIMO)雷达是一种新体制的雷达系统。它借鉴无线通信系统中的MIMO技术,通过收发分集或者波形分集技术突破了传统雷达性能的限制,并实现了更低的截获概率和更高的抗干扰性能,给雷达对抗带来了新的挑战。雷达对抗的前提是侦察,本文主要研究MIMO雷达的侦察与识别。首先从收发模型、信号调制方式、匹配滤波、虚拟阵元和数字波束形成等几个主要方面较为细致地研究了MIMO雷达的工作原理,总结了MIMO雷达的特点。接着研究了雷达侦察系统的组成和工作流程,结合MIMO雷达的特点分析了适合的接收机体制以及参数测量和分选识别方法,讨论了信号脉内特征分析和脉内调制参数提取对于MIMO雷达进一步识别的必要性,并对一种基于瞬时自相关谱的MIMO雷达信号调制类型识别的方法进行了初步的理论研究和仿真。为了更具体的描述一部MIMO雷达,信号的分选和识别需要更多参数的支持。鉴于MIMO雷达信号的混叠现象,本文第四章重点研究了盲源分离算法在MIMO雷达侦察的应用,它将为脉内调制参数测量和估计提供一条途径。首先研究了盲源分离算法的整个过程,分析了一种适用于该算法的雷达侦察模型,然后对该算法提出了增强的信号预处理步骤,即通过最小描述长度准则辅助主分量分析的处理方法,实现信号源数估计、信号降维和降噪,以缩短独立分量分析的计算时间、改善分离效果;以往对于盲源分离的研究中,多数采用简单的实数形式算法,而实际中多为复信号,因此本文采用了复值形式的整套算法,最后对三种MIMO雷达信号进行了分离仿真实验,详细分析了仿真结果,验证了盲源分离算法对于MIMO雷达的进一步识别具有较大意义。
[Abstract]:Multiple input multiple output MIMO (MIMO) radar is a new radar system. Using MIMO technology for reference in wireless communication system, it breaks through the limitation of traditional radar performance by transceiver diversity or waveform diversity technology, and realizes lower probability of interception and higher anti-jamming performance, which brings new challenges to radar countermeasure. The premise of radar countermeasure is reconnaissance. This paper mainly studies the reconnaissance and recognition of MIMO radar. Firstly, the principle of MIMO radar is studied in detail from the aspects of transceiver model, signal modulation, matched filtering, virtual array element and digital beamforming, and the characteristics of MIMO radar are summarized. Then, the composition and work flow of radar reconnaissance system are studied. Combining with the characteristics of MIMO radar, the suitable receiver system and parameter measurement and sorting identification method are analyzed. In this paper, the necessity of signal in-pulse feature analysis and intra-pulse modulation parameter extraction for further identification of MIMO radar is discussed, and a method of signal modulation type recognition based on instantaneous autocorrelation spectrum is preliminarily studied and simulated. In order to describe a MIMO radar more parameters are needed for signal sorting and recognition. In view of the aliasing phenomenon of MIMO radar signals, the fourth chapter focuses on the application of blind source separation algorithm in MIMO radar reconnaissance, which will provide a way for in-pulse modulation parameter measurement and estimation. Firstly, the whole process of blind source separation algorithm is studied, and a radar reconnaissance model suitable for this algorithm is analyzed. Then, an enhanced signal preprocessing step is proposed for the algorithm. That is, by using the minimum description length criterion to assist the processing method of principal component analysis, signal source number estimation, signal reduction and noise reduction can shorten the computation time of independent component analysis and improve the separation effect. Most of them adopt simple real number algorithm, but in practice most of them are complex signals. Therefore, this paper adopts a set of complex value algorithms. Finally, three kinds of MIMO radar signals are separated and simulated, and the simulation results are analyzed in detail. It is verified that the blind source separation algorithm is of great significance for further recognition of MIMO radar.
【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】：TN958
本文编号：2138708
[Abstract]:Multiple input multiple output MIMO (MIMO) radar is a new radar system. Using MIMO technology for reference in wireless communication system, it breaks through the limitation of traditional radar performance by transceiver diversity or waveform diversity technology, and realizes lower probability of interception and higher anti-jamming performance, which brings new challenges to radar countermeasure. The premise of radar countermeasure is reconnaissance. This paper mainly studies the reconnaissance and recognition of MIMO radar. Firstly, the principle of MIMO radar is studied in detail from the aspects of transceiver model, signal modulation, matched filtering, virtual array element and digital beamforming, and the characteristics of MIMO radar are summarized. Then, the composition and work flow of radar reconnaissance system are studied. Combining with the characteristics of MIMO radar, the suitable receiver system and parameter measurement and sorting identification method are analyzed. In this paper, the necessity of signal in-pulse feature analysis and intra-pulse modulation parameter extraction for further identification of MIMO radar is discussed, and a method of signal modulation type recognition based on instantaneous autocorrelation spectrum is preliminarily studied and simulated. In order to describe a MIMO radar more parameters are needed for signal sorting and recognition. In view of the aliasing phenomenon of MIMO radar signals, the fourth chapter focuses on the application of blind source separation algorithm in MIMO radar reconnaissance, which will provide a way for in-pulse modulation parameter measurement and estimation. Firstly, the whole process of blind source separation algorithm is studied, and a radar reconnaissance model suitable for this algorithm is analyzed. Then, an enhanced signal preprocessing step is proposed for the algorithm. That is, by using the minimum description length criterion to assist the processing method of principal component analysis, signal source number estimation, signal reduction and noise reduction can shorten the computation time of independent component analysis and improve the separation effect. Most of them adopt simple real number algorithm, but in practice most of them are complex signals. Therefore, this paper adopts a set of complex value algorithms. Finally, three kinds of MIMO radar signals are separated and simulated, and the simulation results are analyzed in detail. It is verified that the blind source separation algorithm is of great significance for further recognition of MIMO radar.
【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】：TN958
【参考文献】
相关硕士学位论文 前1条
1 王小静;MIMO雷达信号识别与分选方法研究[D];电子科技大学;2013年
，本文编号：2138708
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