低信噪比下MIMO雷达信号参数估计与识别方法研究
发布时间：2019-02-12 23:40
【摘要】：目前,雷达已与通信、导航、电子对抗等系统融为一体,成为高技术信息战场中的重要角色。一批新体制雷达系统别树一帜,并且与传统的常规雷达系统相比,在雷达发射波形、收发天线数、信号处理流程等方面都有明显的区别。新体制雷达抗截获能力得到提高,无疑给电子侦察带来了巨大的挑战,使军方获取信息的能力和各系统联合作战的对抗方式与手段正在发生变革。多输入多输出(Multiple Input Multiple Output,MIMO)雷达正是在这一新的军事需求背景下诞生的一种新体制雷达,受到了各国科研人员越来越多的关注。本论文正是针对上述问题,建立了三种不同调制类型的MIMO雷达信号模型,分析并总结了各子载波信号间的关系以及在不同变换域特征,并以此为基础提出了低信噪比下MIMO雷达参数估计及识别算法。主要内容为:1.分析了MIMO雷达低信噪比特点和三种常用的MIMO雷达信号的时域、频域及时频域特征。同时,分别建立了针对集中式MIMO雷达信号和分布式MIMO雷达信号的侦察模型,为后续信号识别及参数估计奠定基础。2.首先采用时域检测、频域检测及时频域检测方法对集中式MIMO雷达信号和分布式MIMO雷达信号的检测性能进行了探讨。然后,针对简单脉冲MIMO雷达信号(Monopulse-MIMO,MP-MIMO)及线性调频MIMO雷达信号(Linear Frequency Modulation-MIMO,LFM-MIMO),提出了基于子载波合并的参数估计算法。该方法利用MIMO雷达信号的波形分集特征,采用多个子载波合并的方式提高接收信号的信噪比(Signal to Noise Ratio,SNR)。仿真验证了算法的有效性,且该算法能适应更低的SNR环境。3.提出了基于图像处理的集中式MIMO雷达信号识别方法。该方法利用不同调制类型的集中式MIMO雷达信号循环谱和时频谱的差异,采用图像处理的方法对噪声进行抑制,并从中提取出用于识别的特征参数将不同调制类型的集中式MIMO雷达信号与常规雷达信号区别开,并进行了仿真验证了算法的有效性。4.提出了基于信息决策的分布式MIMO雷达体制识别方法。该方法根据分布式MIMO雷达各子载波信号间的关系,并以此作为基础,对截获到的各类雷达信号的辐射源描述字(Emitter Description Word,EDW)进行信息决策,从中识别出分布式MIMO雷达。
[Abstract]:At present, radar has been integrated with communication, navigation, electronic countermeasures and other systems, and has become an important role in high-tech information battlefield. A group of new radar systems are different from conventional radar systems, and there are obvious differences in radar waveform, antenna number, signal processing flow and so on. The enhancement of the anti-interception capability of the new radar undoubtedly brings a great challenge to the electronic reconnaissance and changes the ability of the military to obtain information and the ways and means of the joint operations of various systems. Multi-input multiple-output (Multiple Input Multiple Output,MIMO) radar is a kind of new system radar which is born under the background of this new military requirement and has attracted more and more attention from researchers in many countries. In this paper, three kinds of MIMO radar signal models with different modulation types are established, and the relationship between each subcarrier signal and the characteristics in different transform domain are analyzed and summarized. Based on this, a parameter estimation and recognition algorithm for MIMO radar with low SNR is proposed. The main contents are as follows: 1. The characteristics of low signal-to-noise ratio (SNR) of MIMO radar and the time-domain and frequency-domain characteristics of three commonly used MIMO radar signals are analyzed. At the same time, the reconnaissance models of centralized MIMO radar signal and distributed MIMO radar signal are established respectively, which lays a foundation for the subsequent signal identification and parameter estimation. 2. Firstly, the detection performance of centralized MIMO radar signal and distributed MIMO radar signal is discussed by time-domain detection and frequency-domain detection. Then, a parameter estimation algorithm based on subcarrier combination is proposed for simple pulse MIMO radar signal (Monopulse-MIMO,MP-MIMO) and linear frequency modulated MIMO radar signal (Linear Frequency Modulation-MIMO,LFM-MIMO). In this method, the signal to noise ratio (Signal to Noise Ratio,SNR) of the received signal is improved by using the waveform diversity feature of the MIMO radar signal and the combination of multiple subcarriers. Simulation results show that the algorithm is effective and can adapt to lower SNR environment. 3. 3. A centralized MIMO radar signal recognition method based on image processing is proposed. This method utilizes the difference between cyclic spectrum and time spectrum of centralized MIMO radar signal with different modulation types, and uses image processing method to suppress the noise. The characteristic parameters for identification are extracted to distinguish the centralized MIMO radar signal with different modulation types from the conventional radar signal, and the simulation results show that the algorithm is effective. 4. A distributed MIMO radar system recognition method based on information decision is proposed. Based on the relationship among the sub-carrier signals of distributed MIMO radar, the information decision is made on the emitter description word (Emitter Description Word,EDW) of the captured radar signals, and the distributed MIMO radar is identified.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN957.51
本文编号：2420914
[Abstract]:At present, radar has been integrated with communication, navigation, electronic countermeasures and other systems, and has become an important role in high-tech information battlefield. A group of new radar systems are different from conventional radar systems, and there are obvious differences in radar waveform, antenna number, signal processing flow and so on. The enhancement of the anti-interception capability of the new radar undoubtedly brings a great challenge to the electronic reconnaissance and changes the ability of the military to obtain information and the ways and means of the joint operations of various systems. Multi-input multiple-output (Multiple Input Multiple Output,MIMO) radar is a kind of new system radar which is born under the background of this new military requirement and has attracted more and more attention from researchers in many countries. In this paper, three kinds of MIMO radar signal models with different modulation types are established, and the relationship between each subcarrier signal and the characteristics in different transform domain are analyzed and summarized. Based on this, a parameter estimation and recognition algorithm for MIMO radar with low SNR is proposed. The main contents are as follows: 1. The characteristics of low signal-to-noise ratio (SNR) of MIMO radar and the time-domain and frequency-domain characteristics of three commonly used MIMO radar signals are analyzed. At the same time, the reconnaissance models of centralized MIMO radar signal and distributed MIMO radar signal are established respectively, which lays a foundation for the subsequent signal identification and parameter estimation. 2. Firstly, the detection performance of centralized MIMO radar signal and distributed MIMO radar signal is discussed by time-domain detection and frequency-domain detection. Then, a parameter estimation algorithm based on subcarrier combination is proposed for simple pulse MIMO radar signal (Monopulse-MIMO,MP-MIMO) and linear frequency modulated MIMO radar signal (Linear Frequency Modulation-MIMO,LFM-MIMO). In this method, the signal to noise ratio (Signal to Noise Ratio,SNR) of the received signal is improved by using the waveform diversity feature of the MIMO radar signal and the combination of multiple subcarriers. Simulation results show that the algorithm is effective and can adapt to lower SNR environment. 3. 3. A centralized MIMO radar signal recognition method based on image processing is proposed. This method utilizes the difference between cyclic spectrum and time spectrum of centralized MIMO radar signal with different modulation types, and uses image processing method to suppress the noise. The characteristic parameters for identification are extracted to distinguish the centralized MIMO radar signal with different modulation types from the conventional radar signal, and the simulation results show that the algorithm is effective. 4. A distributed MIMO radar system recognition method based on information decision is proposed. Based on the relationship among the sub-carrier signals of distributed MIMO radar, the information decision is made on the emitter description word (Emitter Description Word,EDW) of the captured radar signals, and the distributed MIMO radar is identified.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN957.51
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