低截获概率雷达侦察信号处理算法研究
发布时间：2019-06-08 14:09
【摘要】：电子对抗中,对截获的雷达信号进行处理是电子智能的一个重要领域。随着电磁环境的日益复杂,低截获概率(Low Probability of Interception,LPI)雷达发展迅速。为有效地对敌方LPI雷达进行侦察和干扰,首先需要对截获的雷达信号进行分析。因此,低截获概率雷达信号处理的理论和算法研究显得日益迫切。本文在总结前人工作的基础上,对典型的LPI雷达信号处理中的若干问题进行了研究,主要内容如下:1.介绍了LPI雷达的相关理论和影响截获概率的各因素,总结了LPI雷达信号处理的研究现状;2.研究了低信噪比条件下,基于分数阶Fourier变换的LFM(Linear Frequency Modulation,LFM)信号参数估计。本文提出了两种插值算法弥补搜索步长和参数离散化的“栅栏效应”带来的缺陷,有效地提高了低信噪比条件下LFM信号参数估计的精度,并在此基础了提出了迭代插值算法,使参数估计精度十分接近CRLB(Cramer-Rao Lower Bound,CRLB)。3.研究了三种典型复杂/复合调制雷达信号的识别算法:LFM/BPSK(Linear Frequecy Modulation and Binary Phase Shift Keying,LFM/BPSK)复合调制信号、FSK/BPSK(Frequency Shift Keying and Binary Phase Shift Keying,FSK/BPSK)复合调制信号和S型非线性调频(Non-linear Frequency Modulation,NLFM)信号。通过对信号的相位和瞬时频率进行特征分析,采用二叉树方法对上述三种复杂/复合调制雷达信号进行了识别分析,并研究了Neyman-Pearson准则下识别门限的选取以及门限对识别概率的影响。4.在实现复杂/复合调制雷达信号识别的基础上,研究了其多参数估计算法。针对复合调制雷达信号:LFM/BPSK复合调制信号和FSK/BPSK复合调制信号,本文采用调制方式分离的方法,首先对信号的相位函数进行乘2处理以去除二相编码信息,以分别得到LFM信号和FSK信号进行参数估计;然后在此基础上分离出BPSK编码信号部分,并采用小波法进行解码。针对S型NLFM信号,主要探讨了其带宽和中心频率的估计方法。5.本文还提出了一种改进型的分段滤波算法用于宽带信号的降噪。通过对信号分段、频移和频域加窗实现宽带信号的频域滤波降噪,算法过程的核心运算为FFT运算,因此易于工程实现。
[Abstract]:In electronic countermeasures, the processing of intercepted radar signals is an important field of electronic intelligence. With the increasing complexity of electromagnetic environment, low probability of interception (Low Probability of Interception,LPI) radar has developed rapidly. In order to effectively detect and interfere with enemy LPI radar, it is necessary to analyze the intercepted radar signal. Therefore, the research on the theory and algorithm of low probability of interception radar signal processing is becoming more and more urgent. On the basis of summing up the previous work, this paper studies some problems in typical LPI radar signal processing, the main contents are as follows: 1. This paper introduces the related theory of LPI radar and the factors that affect the probability of interception, and summarizes the research status of LPI radar signal processing. 2. The parameter estimation of LFM (Linear Frequency Modulation,LFM signal based on fractional Fourier transform under the condition of low signal-to-noise ratio (SNR) is studied. In this paper, two interpolation algorithms are proposed to make up for the "fence effect" caused by the discretization of search step size and parameters, and the accuracy of parameter estimation of LFM signal is effectively improved under the condition of low signal-to-noise ratio (SNR). On this basis, an iterative interpolation algorithm is proposed. The accuracy of parameter estimation is very close to that of CRLB (Cramer-Rao Lower Bound,CRLB). 3. Three typical recognition algorithms of complex / composite modulation radar signals are studied: LFM/BPSK (Linear Frequecy Modulation and Binary Phase Shift Keying,LFM/BPSK) composite modulation signals, FSK/BPSK (Frequency Shift Keying and Binary Phase Shift Keying, FSK/BPSK) composite modulation signal and S-type nonlinear frequency modulation (Non-linear Frequency Modulation,NLFM) signal. Based on the analysis of the phase and instantaneous frequency of the signal, the binary tree method is used to identify and analyze the above three kinds of complex / composite modulation radar signals. The selection of recognition threshold under Neyman-Pearson criterion and the influence of threshold on recognition probability are studied. 4. On the basis of realizing the signal recognition of complex / composite modulation radar, the multi-parameter estimation algorithm is studied. Aiming at the composite modulation radar signal: LFM/BPSK composite modulation signal and FSK/BPSK composite modulation signal, this paper adopts the method of modulation separation. Firstly, the phase function of the signal is multiplied by 2 to remove the two-phase coding information. The parameters of LFM signal and FSK signal are estimated respectively. On this basis, the BPSK encoded signal is separated and decoded by wavelet method. For S-type NLFM signal, the estimation method of bandwidth and center frequency is discussed. 5. In this paper, an improved piecewise filtering algorithm is also proposed to reduce the noise of broadband signals. The frequency domain filtering and noise reduction of broadband signal is realized by dividing the signal, frequency shift and windowing in frequency domain. The core operation of the algorithm is FFT operation, so it is easy to be realized in engineering.
【学位授予单位】：南京航空航天大学
【学位级别】：博士
【学位授予年份】：2014
【分类号】：TN957.51
本文编号：2495344
[Abstract]:In electronic countermeasures, the processing of intercepted radar signals is an important field of electronic intelligence. With the increasing complexity of electromagnetic environment, low probability of interception (Low Probability of Interception,LPI) radar has developed rapidly. In order to effectively detect and interfere with enemy LPI radar, it is necessary to analyze the intercepted radar signal. Therefore, the research on the theory and algorithm of low probability of interception radar signal processing is becoming more and more urgent. On the basis of summing up the previous work, this paper studies some problems in typical LPI radar signal processing, the main contents are as follows: 1. This paper introduces the related theory of LPI radar and the factors that affect the probability of interception, and summarizes the research status of LPI radar signal processing. 2. The parameter estimation of LFM (Linear Frequency Modulation,LFM signal based on fractional Fourier transform under the condition of low signal-to-noise ratio (SNR) is studied. In this paper, two interpolation algorithms are proposed to make up for the "fence effect" caused by the discretization of search step size and parameters, and the accuracy of parameter estimation of LFM signal is effectively improved under the condition of low signal-to-noise ratio (SNR). On this basis, an iterative interpolation algorithm is proposed. The accuracy of parameter estimation is very close to that of CRLB (Cramer-Rao Lower Bound,CRLB). 3. Three typical recognition algorithms of complex / composite modulation radar signals are studied: LFM/BPSK (Linear Frequecy Modulation and Binary Phase Shift Keying,LFM/BPSK) composite modulation signals, FSK/BPSK (Frequency Shift Keying and Binary Phase Shift Keying, FSK/BPSK) composite modulation signal and S-type nonlinear frequency modulation (Non-linear Frequency Modulation,NLFM) signal. Based on the analysis of the phase and instantaneous frequency of the signal, the binary tree method is used to identify and analyze the above three kinds of complex / composite modulation radar signals. The selection of recognition threshold under Neyman-Pearson criterion and the influence of threshold on recognition probability are studied. 4. On the basis of realizing the signal recognition of complex / composite modulation radar, the multi-parameter estimation algorithm is studied. Aiming at the composite modulation radar signal: LFM/BPSK composite modulation signal and FSK/BPSK composite modulation signal, this paper adopts the method of modulation separation. Firstly, the phase function of the signal is multiplied by 2 to remove the two-phase coding information. The parameters of LFM signal and FSK signal are estimated respectively. On this basis, the BPSK encoded signal is separated and decoded by wavelet method. For S-type NLFM signal, the estimation method of bandwidth and center frequency is discussed. 5. In this paper, an improved piecewise filtering algorithm is also proposed to reduce the noise of broadband signals. The frequency domain filtering and noise reduction of broadband signal is realized by dividing the signal, frequency shift and windowing in frequency domain. The core operation of the algorithm is FFT operation, so it is easy to be realized in engineering.
【学位授予单位】：南京航空航天大学
【学位级别】：博士
【学位授予年份】：2014
【分类号】：TN957.51
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