同时多信号环境下欠采样数字测频技术研究

发布时间：2018-06-30 21:09

本文选题：测频 + 数字信道化　；参考：《西安电子科技大学》2014年硕士论文

【摘要】：未来的战争是信息的战争,所以如何快速地在最大程度上获取对方的信息成为电子侦察的主要任务。信号的载频是其中的重要参数,测频的精度决定了后续信号分选与识别时对辐射源的分辨率。数字测频技术实时性好、频率分辨率高、可以处理时域重叠的多信号、系统稳定,基于这些优势,数字测频技术显得越来越重要。侦察接收机处理的目标信号一般具有较大的带宽,使用奈奎斯特采样方法设计系统会产生信号处理速度难以匹配采样速率的问题,可以采用欠采样对信号数字化,但会导致频率模糊,需要使用解模糊算法恢复信号的真实频率。本文首先研究了基于STFT结构的数字信道化技术,讨论了加窗DFT的滤波特性,分析其实现数字信道化的基本原理,给出了算法模型;并且以输入信号为单载频和线性调频信号为例,仿真分析了算法的工作流程,给出了信号时域及频域参数的估计方法;接下来详细讨论了STFT算法中的一些问题,例如检测门限的设定、窗函数长度选择、滑动点数的确定等问题,分析了不同参数产生的影响,便于使算法在满足系统性能指标要求的前提下具有较高的工作效率;讨论了基于STFT信道化对雷达信号调制方式的分析识别,给出了可用的分选准则;讨论了三种信道化后的精测频算法,并分别对算法的性能进行了仿真分析;研究了在同时多信号情况下大信号对小信号的影响,分析了窗函数的作用并给出了窗函数的选择依据。最后在欠采样的条件下,讨论了欠采样产生频率模糊的原因,给出四种典型的解模糊结构,包括单通道延迟法、正交双通道延迟法、双速率解模糊法与MUSIC解模糊算法;分别仿真了解模糊过程,分析了解模糊原理,并指出了各自的优缺点;提出了将STFT信道化与欠采样结合使用的测频方法,并以双速率解模糊为例,仿真验证方法的可行性,给出使用时的注意事项,对实际硬件实现有借鉴意义。
[Abstract]:The future war is the war of information, so how to obtain the information of the other party quickly becomes the main task of electronic reconnaissance. The carrier frequency of the signal is an important parameter. The accuracy of the frequency measurement determines the resolution of the emitter when the subsequent signal is sorted and identified. Digital frequency measurement technology is more and more important because of its good real-time performance and high frequency resolution. It can deal with multi-signal overlapping in time domain and the system is stable. Based on these advantages, digital frequency measurement technology is becoming more and more important. The target signal processed by the reconnaissance receiver generally has a large bandwidth. Using Nyquist sampling method to design the system will cause the problem that the signal processing speed is difficult to match the sampling rate, so the under-sampling can be used to digitize the signal. But it can cause the frequency blur, so it is necessary to restore the true frequency of the signal by using the deblurring algorithm. In this paper, the digital channelization technology based on STFT structure is studied, the filtering characteristic of windowed DFT is discussed, the basic principle of digital channelization is analyzed, and the algorithm model is given. Taking input signal as single carrier frequency signal and linear frequency modulation signal as an example, the working flow of the algorithm is simulated and the estimation method of signal parameters in time domain and frequency domain is given. Then, some problems in STFT algorithm are discussed in detail. For example, the setting of detection threshold, the selection of window function length, the determination of sliding points and so on. The influence of different parameters is analyzed, which makes the algorithm more efficient on the premise of meeting the requirements of system performance. This paper discusses the analysis and identification of radar signal modulation mode based on STFT channelization, presents the available sorting criteria, discusses three kinds of fine frequency measurement algorithms after channelization, and analyzes the performance of the algorithm by simulation. The influence of large signal on small signal in the case of simultaneous multi-signal is studied. The function of window function is analyzed and the selection basis of window function is given. Finally, under the condition of undersampling, the causes of frequency ambiguity are discussed, and four typical structures are given, including single channel delay method, orthogonal double channel delay method, dual rate deblurring method and music deblurring algorithm. The fuzzy process is simulated, the fuzzy principle is analyzed, and their advantages and disadvantages are pointed out, and a frequency measurement method which combines STFT channelization with under-sampling is proposed, and the feasibility of the method is verified by simulation. The points for attention in use are given, which can be used for reference in practical hardware implementation.
【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】：TN971.1

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