一类随机过程基于强跟踪滤波的算法研究  

Research on an Estimation Algorithm of Non-stationary Random Process Based on Strong Tracking Filter

作　　者：余利文[1] 

机构地区：[1]杭州电子科技大学信息与控制研究所,浙江杭州310018

出　　处：《杭州电子科技大学学报（自然科学版）》2009年第6期83-86,共4页Journal of Hangzhou Dianzi University：Natural Sciences

基　　金：浙江省自然科学基金资助项目(Y1080422)

摘　　要：该文以一类观测系统为研究对象,首先在对被观测信号的随机特性统计分析的基础上,建立描述其变化的动态模型;然后针对信息缺乏情况下所建动态模型存在精度不高的实际情况,通过引入强跟踪滤波技术,实现了对被测目标状态与未知参数的联合估计;最后通过仿真对新方法与已有方法进行比较,验证了新方法的有效性。This paper researches on a system which only providing the observation signals.Firstly,The dynamic model is established by using the statistical characteristics of random signals,and then introduces the idea of strong tracking filter into this system because the existing models and methods are not precision,achieving the joint-estimation of observed object state and unknown parameter;Finally,simulated experimental results show that the proposed approach can guarantee higher precision compared with tradition...

关 键 词：观测系统 随机信号 状态与参数联合估计 强跟踪滤波 

分 类 号：TP11[自动化与计算机技术—控制理论与控制工程]