【作者】 钱眺；

【导师】 茅玉龙；

【作者基本信息】 南京信息工程大学 ， 信号与信息处理， 2008， 硕士

【摘要】 敌我识别(IFF)信号是飞行器与地面站之间进行身份识别和信息交换的信号。在现代战争中,敌我识别信号可以作为获取敌方军事情报的重要来源;在民用机场的空中管制,在和平时期的国与国对峙、局部突发事件中,都会面临大量的IFF信号分析与识别的问题。本文以敌我识别系统工作时的信号为研究重点,首先简要介绍了三种模式的敌我识别系统,分析了一次雷达与二次雷达的区别,阐述了二次雷达敌我识别系统的结构、原理及单脉冲等关键技术。在此基础上,对IFF信号时域有意义的特征如脉冲宽度、脉冲高度、脉冲间隔、信号长度进行了分析,在频域方面用快速傅里叶变换与韦尔奇谱估计方法对信号的频谱与功率谱信息进行了提取与比较。本文给出了对IFF信号处理与识别的详细方案,将待测信号通过中频采样正交接收机,比较了基于频率中心法与经相位修正的DFT测频法对载频测定优劣,将分为I、Q两路的信号进行求模和相位计算,得出信号包络和瞬时相位。模式识别程序对信号进行单脉冲特征的提取,对不具备脉冲特征的信号优先做出排除,并根据不同信号的脉内特征进行模式识别,本文对识别部分的特征提取与识别过程给出了详细的处理流程图。在时频域分析信号时本文做了大量的仿真实验,同时提出的信号处理和模式识别的方法在实验中也均有验证。本文对不同的信噪比下的识别情况进行了蒙特卡罗仿真,实验结果表明,本文提出的信号处理及识别方法能够有效识别IFF信号。本文在最后介绍了用MATLAB的GUI组件制作的IFF信号分析与识别的演示系统,用于辅助信号的分析与识别。更多还原

【Abstract】 IFF signals are the type of signals to exchange message and military recognition, which are used between aerostat and the station on earth. In time of war, they are the most important resources to get the information of enemy. Besides, IFF signals are applied to many other domains. For examples, we can use IFF signals on Air Traffic Control, on confronting each other between states at peacetime, and so on.The emphasis of this thesis was based on the signals of IFF systems at different mode. At the beginning of the thesis, three kind of IFF systems were introduced. Then, the thesis analyzed similarities and differences of primary radar systems and the secondary radar systems; also the working principle structure and the key technique such as mono-pulse of the SSR were expatiated. When one SSR system works, the working manner of enquiry and responding is distinguished. On the basis of these conceptions, the thesis studied the minute features of IFF signals on time domain, such as length and height of the pulse, pulse envelop of the signal, and time slot between the pulses. The minute features of frequency domain were also compared and distilled with Power Spectral Density estimate. At the thesis, an effect method of processing and identifying IFF signals was presented. One character of IFF signals is mono-pulse, so if one signal does not have this character, the signal could be removed from the queue of the IFF signals first. At the end, the signals with the mono-pulse character could be identified by other minute features of time frequency domain. The idiographic flow chart of processing and identifying IFF signals were presented at the thesis.There were lots of experiment for analyzing signals both in time domain and frequency domain, and the methods raised in the thesis for processing and identifying was also used in tests. The Monte Carlo simulation of detecting rate of correctly identified at different SNR is very important, because the methods for processing and identifying IFF signals were validated. At the end of the thesis, an assistant demo system made by the GUI was introduced to study and analyze IFF signals.更多还原