基于一阶统计矩的数字通信信号调制方式的自动识别

数字通信信号调制方式的自动识别在军用和民用方面都具有十分重要的意义。为了能自动识别MASK、MFSK、MPSK和MQAM四类信号，本文基于截获信号的一阶统计矩，提出七个特征参数，它们均可利用常规信号处理技术得到，与基于二阶或高阶矩的其它特征参数相比，这些参数提取过程具有计算量小、提取方便的优点。给出四类信号调制方式自动识别算法的实现流程，该识别算法以判决理论为基础，不要求实现码元同步。仿真结果证明，在信噪比≥7dB时，识别算法的平均识别成功率＞97%，性能明显优于同类算法，有望用于实际的非协作通信系统中信号的检测和快速识别。 

Automatic Modulation Recognition of Digital Communication Signals Based on the First Statistical Moments

Automatic modulation recognition of digital communication signals is extremely important for both military and civilian purposes. In this paper, seven key features based on the first statistical moments of the intercepted signals are proposed to automatically recognize MASK (M-ary Amplitude Shift Keying), MFSK (M-ary Frequency Shift Keying), MPSK (M-ary Phase Shift Keying) and MQAM (M-ary Quadrature Amplitude Modulation) signals. All these key features are calculated using the conventional signal processing methods. Compared to those based on the second or even higher order moments, the calculation of the proposed seven key features used in the modulation recognition algorithm has been less complicated and more efficient. A modulation identification algorithm based on the decision-theoretic approach is also developed which removes the need for symbol synchronization. Computer simulations have been carried out.? It has shown that all the aforementioned four types of digital communication signals have been recognized with average success rate ＞97% at SNR≥7dB. Thus it is superior to some other algorithms and is suitable for the practical application of signal detection and fast recognition in non-cooperation communication systems.