利用迭代滤波改进乘积高阶模糊函数  

Improvement on Product High-Order Ambiguity Function by Iterative Filtering

作　　者：谭小刚[1] 魏平[1] 李立萍[1] 

机构地区：[1]电子科技大学电子工程学院,成都610054

出　　处：《电子科技大学学报》2009年第2期182-185,共4页Journal of University of Electronic Science and Technology of China

基　　金：教育部新世纪优秀人才计划资助(NCET-05-0803);信息综合控制国家级重点实验室基金

摘　　要：乘积高阶模糊函数(PHAF)是因分析mc-PPS而提出来的,但它抑制交叉项的能力有限,难以实现mc-PPS估计。该文提出了逐次滤除最强PHAF峰对应的分量来减少交叉项的迭代滤波方法,改进后的PHAF具有较好的鲁棒性:减少了估计盲区,并且具有更好的估计精度,降低了信噪比门限,而且能估计低阶相位系数,这些性能由多个mc-PPS仿真例子所验证。The product high-order ambiguity function （PHAF）, originally proposed for analyzing multicomponent polynomial phase signal （mc-PPS）, is still troubled by interference terms in the estimation of mc-PPS. In this paper, a scheme to mitigate interference terms is proposed by iteratively filtering all the components corresponding to the strongest peak of the PHAF. The improved version of PHAF has better precision and smaller blind area and threshold of signal to noise ratio, and can estimate lower order phase coefficients. The performance of the new method is verified by simulations with mc-PPS＇s.

关 键 词：迭代滤波 交叉项 多分量多项式相位信号 参数估计 乘积高阶模糊函数 

分 类 号：TN911.72[电子电信—通信与信息系统]