摘要
提出了一种现代互谱估计方法——基于互谱自回归(AR)模型参数估计的SVD算法,相比作者之前提出的基于互谱AR模型参数估计的Levinson算法,本文提出的方法有效地克服了互相关函数rxy(m)估计误差带来的影响。仿真结果表明:谱估计精度有了很大提高。搭建了测量噪声背景下的仿真平台,对基于该方法的变换域通信系统(TDCS)抗干扰性能进行了仿真研究。结果表明:该方法下TDCS能够有效地抑制测量噪声,在不同干扰下的误码率大大降低,提高了抗干扰能力。
A modern cross spectrum estimation method is proposed, which is the SVD algorithm based on cross-spectrum of the Auto-Regressive （AR） model for parameter estimation. Compared to previously proposed Levinson algorithm based on cross-spectrum of the AR model, the new method of this study can effectively overcome the influence of the estimation error of the cross correlation function r~ （m）. Simulation results show that the spectrum estimation accuracy of the proposed method is much better. A simulation platform in the measurement noise background is established. The anti-jamming performance of the Transform Domain Communication System （TDCS） based on the proposed method is studied. The results show that the TDCS can effectively suppress the measurement noise, greatly reduce the error rate under different disturbances, and improve the capacity of antidisturbance.
出处
《吉林大学学报（工学版）》
EI
CAS
CSCD
北大核心
2014年第5期1423-1428,共6页
Journal of Jilin University:Engineering and Technology Edition
基金
吉林省博士后科研项目(RB201336)
关键词
通信技术
变换域通信系统
自回归模型
误码率
communication technology
transform domain communication system
autoregressivemodel
error rate
