基于星座图的PSK、QAM信号联合识别算法应用

Application of joint signal recognition on PSK and QAM based on constellation

针对PSK、QAM信号的理论识别算法在实际应用系统中不能满足较高的识别精度这一问题,提出一种基于星座图的PSK、QAM信号联合识别算法。该算法首先对信号同步处理并恢复信号星座图,然后进行相位统计与星座图聚类,提取出星座图的中心点个数N、相位个数P以及最大半径与最小半径比R等特征参数,再构造评估函数C(N,R,P)以识别PSK、QAM信号的调制方式。实际应用表明,对码元数目大于800的PSK和QAM信号的识别准确率均高于94%;对信噪比为8.25 d B的860M数字集群TETRA信号的识别率高达94.12%。该算法流程清晰且不需要任何先验知识,非常适合实际应用,此方法已经在某公司的信号分析系统上得到了应用。

The theoretical recognition algorithms on PSK and QAM couldn＇ t reach high identification precision when it applied to real system. Therefore, this paper proposed a joint recognition algorithm on PSK and QAM based on constellation. The algorithm firstly did signal synchronization and recovered the constellation. By counting the phase and constellation clustering, it extracted the centre point number of the constellation as N, the phase number P, as well as the ratio of the maximal and the minimal radius as R. After that, it structured evaluation function C（N,R,P） to recognize PSK and QAM. Practical application shows, the identification rate of PSK and QAM is higher than 94% when symbols are more than 800, and the identification rate of the 860M digital clustering TETRA signals reaches up to 94.12%. This algorithm is suitable for practical application because its＇ flow is clear and it doesn＇ t need any prior knowledge. Now it has been applied to the signal analysis system of some company.