跳频信号特征提取及信号分选方法的研究
发布时间：2019-04-23 09:51
【摘要】：无线通信是现代军事作战的主要方式,为了使得通信能够安全可靠的进行,跳频通信技术应运而生。跳频通信技术因其优越的特性,受到各国军方的极度重视,各方都在积极的进行对跳频通信技术的研究,并且取得了巨大的进步。由于实际的作战环境比较复杂,截获的信号中往往不只一个跳频信号,为了完成作战使命,必须要将截获到的混合信号分选开来,这样便可以得知单个跳频信号的有用信息。然而信号分选的效果则取决于跳频信号参数估计结果的准确性以及分选算法的优劣,由此可知,跳频信号的特征参数提取及分选于实际作战应用而言是至关重要的两个方面,开展对这两个方面的研究具有深远的意义,本文将围绕单天线接收和阵列天线接收两个方向来展开研究。在特征参数提取环节,由于实际的通信环境比较复杂,通常存在着各种干扰信号及噪声,因此需要首先进行跳频信号的预处理,对截获的信号进行时频分析,然后将其灰度化,利用形态学处理方法来剔除干扰信号及噪声,为后续工作的展开提供了干净的跳频信号;接下来着重分析研究了单天线接收情况下的基于二次差分算法和SDIF算法相结合的跳频信号的参数估计,以及阵列天线接收情况下的基于MUSIC算法的DOA估计;最后经由仿真实验证实了本文算法的准确性以及有效性。在跳频信号分选的环节,针对不同的情况,本文分析研究了不同的分选算法。首先研究了基于滤波法的跳频信号分选,用于处理不同跳频信号的跳频频率集之间没有交叉的情况,此方法的应用虽然受限较大,但是在这种特定情况下能够很好的对信号进行分选,操作简单,效果良好;其次研究了基于时间到达法的信号分选方法,此方法计算量小,易于实时分选,但只能应用于异步组网的情况;接着研究了基于时频域信息和时频空域信息的跳频信号分选,利用CDIF算法和CT序列搜索相结合的方法实现了跳频信号的分选;最后对基于聚类的跳频信号分选方法展开了重点的研究,对几种常见的聚类算法的优缺点进行了分析比较,本文是在传统KHM聚类算法的基础上进行了改进,并且通过仿真实验验证了该算法的准确性以及可行性。
[Abstract]:Wireless communication is the main way of modern military combat. In order to make communication safe and reliable, frequency hopping communication technology emerges as the times require. Because of its superior characteristics, frequency hopping communication technology has been attached great importance to by the military of various countries. All parties are actively carrying on the research on frequency hopping communication technology, and have made great progress. Because of the complexity of the actual combat environment, the intercepted signal usually contains more than one frequency hopping signal. In order to accomplish the combat mission, it is necessary to separate the intercepted mixed signals, so that the useful information of a single frequency hopping signal can be obtained. However, the effect of signal sorting depends on the accuracy of the parameters estimation results of frequency hopping signals and the advantages and disadvantages of sorting algorithms. Therefore, the extraction and sorting of the characteristic parameters of frequency hopping signals are two important aspects in practical combat applications. It is of great significance to carry out the research on these two aspects. This paper will focus on the single antenna receiving and the array antenna receiving. In the process of feature parameter extraction, due to the complexity of the actual communication environment, there are usually a variety of interference signals and noises, so it is necessary to pre-process the frequency-hopping signals, analyze the intercepted signals in time-frequency domain, and then turn them into grayscale. The method of morphological processing is used to eliminate the interference signal and noise, which provides a clean frequency hopping signal for the subsequent work. Then the parameter estimation of frequency hopping signal based on the combination of quadratic difference algorithm and SDIF algorithm in the case of single antenna receiving and the DOA estimation based on MUSIC algorithm in the case of receiving array antenna are analyzed and studied. Finally, the accuracy and effectiveness of the proposed algorithm are verified by simulation experiments. In the process of frequency hopping signal sorting, according to different conditions, different sorting algorithms are analyzed and studied in this paper. Firstly, the frequency hopping signal sorting based on filtering method is studied, which is used to process the frequency hopping frequency sets of different frequency hopping signals without crossover. Although the application of this method is very limited, But in this particular case, the signal can be sorted very well, the operation is simple, and the effect is good. Secondly, the signal sorting method based on time-arrival method is studied. This method is easy to be sorted in real-time, but it can only be used in asynchronous networking. Secondly, the frequency-hopping signal sorting based on time-frequency domain information and time-frequency domain information is studied. The sorting of frequency-hopping signal is realized by combining CDIF algorithm and CT sequence search. Finally, this paper focuses on the sorting method of frequency-hopping signals based on clustering, analyzes and compares the advantages and disadvantages of several common clustering algorithms, and improves on the basis of the traditional KHM clustering algorithm. The accuracy and feasibility of the algorithm are verified by simulation experiments.
【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】：TN914.41
本文编号：2463359
[Abstract]:Wireless communication is the main way of modern military combat. In order to make communication safe and reliable, frequency hopping communication technology emerges as the times require. Because of its superior characteristics, frequency hopping communication technology has been attached great importance to by the military of various countries. All parties are actively carrying on the research on frequency hopping communication technology, and have made great progress. Because of the complexity of the actual combat environment, the intercepted signal usually contains more than one frequency hopping signal. In order to accomplish the combat mission, it is necessary to separate the intercepted mixed signals, so that the useful information of a single frequency hopping signal can be obtained. However, the effect of signal sorting depends on the accuracy of the parameters estimation results of frequency hopping signals and the advantages and disadvantages of sorting algorithms. Therefore, the extraction and sorting of the characteristic parameters of frequency hopping signals are two important aspects in practical combat applications. It is of great significance to carry out the research on these two aspects. This paper will focus on the single antenna receiving and the array antenna receiving. In the process of feature parameter extraction, due to the complexity of the actual communication environment, there are usually a variety of interference signals and noises, so it is necessary to pre-process the frequency-hopping signals, analyze the intercepted signals in time-frequency domain, and then turn them into grayscale. The method of morphological processing is used to eliminate the interference signal and noise, which provides a clean frequency hopping signal for the subsequent work. Then the parameter estimation of frequency hopping signal based on the combination of quadratic difference algorithm and SDIF algorithm in the case of single antenna receiving and the DOA estimation based on MUSIC algorithm in the case of receiving array antenna are analyzed and studied. Finally, the accuracy and effectiveness of the proposed algorithm are verified by simulation experiments. In the process of frequency hopping signal sorting, according to different conditions, different sorting algorithms are analyzed and studied in this paper. Firstly, the frequency hopping signal sorting based on filtering method is studied, which is used to process the frequency hopping frequency sets of different frequency hopping signals without crossover. Although the application of this method is very limited, But in this particular case, the signal can be sorted very well, the operation is simple, and the effect is good. Secondly, the signal sorting method based on time-arrival method is studied. This method is easy to be sorted in real-time, but it can only be used in asynchronous networking. Secondly, the frequency-hopping signal sorting based on time-frequency domain information and time-frequency domain information is studied. The sorting of frequency-hopping signal is realized by combining CDIF algorithm and CT sequence search. Finally, this paper focuses on the sorting method of frequency-hopping signals based on clustering, analyzes and compares the advantages and disadvantages of several common clustering algorithms, and improves on the basis of the traditional KHM clustering algorithm. The accuracy and feasibility of the algorithm are verified by simulation experiments.
【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】：TN914.41
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