基于分数低阶统计量的时延估计算法比较  

Compare of time-delay estimation algorithm based on fractional lower-order statistics

作　　者：汤勇[1] 熊兴中[1] 

机构地区：[1]四川理工学院自动化与电子信息学院,自贡643000

出　　处：《电子测量技术》2014年第8期65-69,共5页Electronic Measurement Technology

基　　金：四川省杰出青年基金(2011JQ0034);四川省省属高校科研创新团队建设计划基金(13TD0017);人工智能四川省重点实验室基金(2012RYJ05)资助项目

摘　　要：传统的时延估计算法大多建立在高斯模型的基础上,这种情况下,利用信号的二阶、高阶统计量,可以得到理想的结果。然而,研究的信号往往都处在非高斯环境下,如通信线路瞬间尖峰、环境噪声等。这一类信号的时域波形中存在一个明显的峰值,这时利用α稳定分布模型可以较好地表述非高斯脉冲信号和噪声。所以有必要对α稳定分布模型下的,基于分数低阶统计量(FLOS)的时延估计算法进行研究。目前,基于分数低阶统计量的时延估计算法还有许多尚未完善的地方,通过对现有的几种基于分数低阶统计量的时延估计算法进行仿真,就几种算法的效果以及适用范围进行了研究。在通过计算机仿真的基础上,得出结论,从而对实际应用具有一定的参考价值。Lots of traditional time-delay estimation algorithms are based on Gaussian model. In this case, the use of second-order and higher-order estimator of signal can get the desired results. However, the actual situation of non- Gaussian noise is often, such as communications line instant spikes, ambient noise, and so on. These signs have significant spikes in the time-domain waveform. At this moment,alpha stable distribution model can be a better way to describe this type of non-Gaussian pulse signal and noise. Therefore, it is necessary to study the time-delay estimation algorithm based on fractional lower-order statistics（FLOS） in alpha stable distribution model. Currently, there are many places yet to be perfected in the time-delay estimation algorithm based on fractional lower-order statistics. Based on the simulation of several existing time delay estimation algorithm based on fractional lower order statistics, as well as on the effect of several algorithms scope studied. On the basis of computer simulation, draw conclusions, and thus has a certain reference value for practical applications.

关 键 词：时延估计 分数低阶 非高斯噪声 Α稳定分布 

分 类 号：TN911[电子电信—通信与信息系统]