摘要
本文对频偏和相偏参数未知的幅相调制信号的识别问题,提出了一种新的基于似然函数的方法。该方法引入一种自适应的马尔可夫链蒙特卡罗(MCMC)算法——自适应Metropolis(AM)算法,可产生满足目标分布的未知参数的各态历经样本从而实现似然函数的近似计算。仿真试验表明算法具有很好的收敛性和识别精度。
In this paper, a new likelihood-based method for classifying phase-amplitude-modulated signals with unknown phase and frequency offset is proposed. The method introduces a new Markov Chain Monte Carlo （MCMC） algorithm, called the Adaptive Metropolis （AM） algorithm, to directly generate samples of the target posterior distribution and implement the multidimensional integrals of likelihood function. Simulation results show that the proposed method has the advantages of high accuracy and robustness to phase and frequency offset.
出处
《网络安全技术与应用》
2013年第1期46-49,39,共5页
Network Security Technology & Application
