现代互谱估计方法及仿真分析

发布时间：2018-07-01 11:45

本文选题：通信技术 + 变换域通信系统　；参考：《吉林大学学报(工学版)》2014年05期

【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。
[Abstract]:In this paper, a modern cross-spectral estimation method-SVD algorithm based on cross-spectral autoregressive (AR) model parameter estimation is proposed, which is compared with Levinson algorithm based on cross-spectral AR model parameter estimation. The method proposed in this paper effectively overcomes the influence of rxy (m) estimation error of cross-correlation function. The simulation results show that the accuracy of spectral estimation has been greatly improved. The simulation platform of measurement noise is built, and the anti-jamming performance of transform Domain Communication system (TDCS) based on this method is simulated. The results show that TDCS can effectively suppress the measurement noise, reduce the bit error rate under different interference, and improve the anti-jamming ability.
【作者单位】：吉林大学通信工程学院;
【基金】：吉林省博士后科研项目(RB201336)
【分类号】：TN911.23

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