摘 要

调制识别技术是通信系统中不可或缺的重要部分，在民用和军事方面应用广泛。非协作通信技术的迅速发展促使调制信号的类型日益丰富，通信环境也日益恶劣，如何优化识别算法以实现低信噪比下的调制识别引起了国内外众多学者的关注。

本文基于特征提取的统计模式识别算法和决策理论，研究了包括数字信号和模拟信号在内共16种信号的调制识别问题。主要内容和工作分为以下几个部分：

1. 研究了待识别信号集中各信号的时频域特性，并结合不同调制识别特征的基础理论，对信号进行数字下变频或Hilbert变换预处理。
2. 基于时频域特征识别理论实现了模拟信号AM、FM、LSB、USB以及FSK信号的识别，并从中分离出PSK信号。其中，提出了一种谱峰数目统计法，提高了FSK和PSK信号的正确识别率；
3. 基于高阶累积量特征的定义，分别研究了和信号的高阶累积量，完成的类内识别以及部分信号的类内识别；
4. 基于星座图特征和减法聚类算法，进一步解决QAM信号的类间识别问题。最后结合各调制识别算法的优缺点，制定了调制识别总方案。仿真结果显示，当时，所有调制信号的识别率均高于，其中，时信号的识别率可达100%，验证了本文信号识别方案的良好性能。

关键词：调制识别；瞬时信息；高阶累积量；星座图聚类

Abstract

Modulation recognition technology is an indispensable part of communication system, which is widely used in civil and military fields, such as signal recognition spectrum detection and electronic reconnaissance. With the rapid development of non-cooperative communication technology, signal modulation methods are increasingly diverse and the communication environment is increasingly complex. How to optimize the recognition algorithm to realize modulation recognition under low SNR has attracted the attention of many scholars at home and abroad.

Based on the statistical pattern recognition algorithm and decision theory of feature extraction, this paper studies the modulation recognition of 16 kinds of signals, including digital signals and analog signals. The main contents and work are divided into the following parts:

1. This paper studies the time-frequency characteristics of the signals in the signal set to be recognized, and combined with the basic theory of different modulation recognition characteristics, the signal was preprocessed by digital down-conversion or Hilbert transformation.
2. Based on the time-frequency domain feature recognition theory, the recognition of analog signal AM FM LSB USB and FSK signal is realized, and the PSK signal is separated from them. Among them, a spectrum peak number statistics method is proposed to improve the correct recognition rate of FSK and PSK signals.
3. Based on the definition of high order cumulants, the high order cumulants of PSK and QAM signals are studied, and the recognition of PSK and part of QAM signals is realized.
4. Based on the constellation features and subtractive clustering algorithm, the problem of inter-class recognition of QAM signals is further solved. Finally, combining the advantages and disadvantages of each modulation recognition algorithm, the modulation recognition scheme is developed. Simulation results show that the recognition rate of all signals is higher than 95% when , and the recognition rate of QAM signal can reach 100 even under low SNR, which verifies the good performance of the signal recognition scheme.

Key Words：Modulation recognition；Instantaneous information；High order cumulants；Constellation clustering

目录

第一章 绪论 1

1.1研究背景与意义 1

1.2国内外研究现状 2

1.3论文结构与内容安排 3

第二章 调制识别技术理论基础 5

2.1引言 5

2.2模拟调制技术 5

2.2.1幅度调制（AM） 5

2.2.2频率调制（FM） 6

2.2.3单边带调制（SSB） 7

2.3数字调制技术 7

2.3.1幅度键控（ASK） 7

2.3.2频移键控（FSK） 8

2.3.3相移键控（PSK） 10

2.3.4正交幅度调制（QAM） 11

2.4信号的预处理 12

2.5本章小结 13

第三章 基于时频域特征参数的调制识别 14

3.1引言 14

3.2瞬时信息的提取 14

3.3特征参数的提取 15

3.4识别流程及识别结果 18

3.4.1决策论识别流程 18

3.4.2仿真结果 19

3.5本章小结 24

第四章 基于高阶累积量及星座图的联合调制识别 25

4.1引言 25

4.2高阶累积量特征 25

4.2.1高阶矩和高阶累积量的定义 25

4.2.2数字信号的高阶累积量 27

4.3基于星座图调制识别原理 27

4.3.1星座图特征 27

4.3.2减法聚类算法 28

4.4 MPSK、MQAM信号的类内识别 29

4.4.1 MPSK信号的类间识别 29

4.4.2MQAM信号的类间识别 31

4.5通信信号调制识别的实现 34

4.5.1调制识别总方案 34

4.5.2仿真结果与分析 36

4.6本章小结 37

第五章 总结与展望 38

5.1总结 38

5.2展望 38

参考文献 39

致谢 41

第一章 绪论

1.1研究背景与意义

通信即收发双方间信息的交互，其目的在于及时、有效、可靠、实时地将信息通过通信信道顺利传输到接收方^[1]。早期的传统通信系统大多采用协作方式，即通信的收发双方事先约定了载波频率、调制类型等先验知识，接收方可以直接对信号进行解调等处理。在通信的发展史中，为了提高信道利用率、提高频谱利用率以满足各种通信要求，通信信号的调制种类向多样化的方向发展；与此同时，复杂的通信环境和严重的噪声干扰给无线通信带来了巨大的挑战。因此，从技术角度上来说，通信信号的调制识别技术在非协作通信系统中起着关键性的作用。

信号调制方式的识别是信号检测和解调之间不可或缺的关键。其功能在于：在有噪声干扰和信号其他参数未知的情况下，根据某种识别算法对信号进行分析，并对信号的调制类型做出判断，为后续的信号处理准备条件^[2]。