非合作通信中信号检测及调制识别的关键技术研究

Signal Detection and Modulation Recognition are the key technologies of receivers in non-cooperative communication system, which have the important application value in adaptive modulation, military reconnaissance and electronic countermeasure fields. Aiming at the problems that current signal detection and modulation recognition technologies have poor performance and could not meet the requirement of practical application in non-cooperative communication, The project will research on the de-noising processing method of co-channel time-frequency overlapped multi-signal based on adaptive stochastic resonance, explore the parameter estimation method based on cyclo stationarity for co-channel time-frequency overlapped multi-signal; and try to research the modulation recognition method based on cloud model and hidden Markov model based on relative margin for co-channel time-frequency overlapped multi-signal. Combining the cyclo stationarity feature extraction theory and feature selection theory based on culture genetic algorithm, the project will also explore the robust recognition method of single carrier signals in complex communication environment. Meanwhile, the project will also research on the sub-carrier modulation recognition method with comparing the variance of sequences in the minimum ring of vectogram through analyzing the effect of pilots and frequency offset on sub-carrier modulation recognition. Based on all the research, the project will also give a set of complete system scheme of detection and recognition for digital modulation signals and evaluate the performances of the proposed methods in various application environments by computer simulation and design the IP core for some key parts, which provide the basis of theory and application for signal detection and digital modulation recognition in non-cooperative system and electronic countermeasure field.

信号检测及调制识别技术是非合作通信中接收机的关键技术，在自适应调制、军事侦察、电子对抗中有重要的应用价值。针对目前非合作通信中信号的检测与识别性能低且不能满足实际应用需求的问题，本项目研究基于自适应随机共振的时频重叠信号消噪方法，探索基于循环平稳特性的混合信号的参数估计方法，并尝试研究基于云模型与相对界隐马尔可夫模型的混合信号调制识别方法。此外，结合循环平稳特征提取理论和基于文化遗传算法的特征选择理论，探索复杂通信环境下单载波调制信号的稳健识别方法。并通过分析导频和频偏对OFDM信号的子载波识别特性的影响，研究基于矢量图最小环带模值方差的OFDM信号子载波调制方式识别方法。在此基础上，给出完整的数字调制信号检测及识别的系统方案，通过计算机仿真评估算法在各种应用环境中的性能，并将对其中的一些关键部分进行IP core设计，为信号检测和数字调制识别在非合作通信系统和电子对抗领域的应用提供理论。

信号检测及调制识别技术是非合作通信中接收机的关键技术，在自适应调制、军事侦察、电子对抗中有重要的应用价值。本项目研究了单通道时频重叠信号的分量个数、载波频率、码元速率和信噪比等参数的估计，并对单通道时频重叠信号的调制方式识别、多径信道下MQAM信号的调制方式识别、多径信道下含有频偏相偏信号的调制方式识别、非高斯噪声下数字调制信号识别、含有导频的OFDM子载波调制方式识别和含有小数倍频偏的OFDM子载波的调制方式识别分别进行了研究，分别提出了有效可行的方法，并通过计算机仿真评估所提方法在各种应用环境中的性能，并将对其中的一些关键部分进行IP core设计，为信号检测和数字调制识别在非合作通信系统和电子对抗领域的应用提供理论基础。