随机丢包的无迹卡尔曼滤波估计以及性能分析  

Estimation and Performance Analysis of Unscented Kalman Filter with Randomly Missing Measurements

作　　者：白睿 任祝 BAI Rui;REN Zhu(School of Computer Science and Technology,Zhejiang Sci-Tech University,Hangzhou 310018,China;School of Information Science and Engineering,Zhejiang Sci-Tech University,Hangzhou 310018,China)

机构地区：[1]浙江理工大学计算机科学与技术学院,浙江杭州310018 [2]浙江理工大学信息科学与工程学院,浙江杭州310018

出　　处：《电子科技》2024年第2期23-29,共7页Electronic Science and Technology

基　　金：国家自然科学基金(61403347)。

摘　　要：在工程应用中,无线网络控制系统多为非线性系统。由于长距离传输和通信网络不可靠等原因,系统传感器的测量值可能在传输过程中丢失,影响精度估计以及系统性能。文中研究一类受相关噪声和传感器测量值丢失影响的非线性离散随机系统的无迹卡尔曼滤波问题。通过引入一个服从伯努利分布且条件概率已知的随机变量来描述随机发生的传感器测量值丢失现象。文中提出了一种对数据进行补偿的算法,并使用标准数值软件对所得结果进行验证。结果表明,经过算法补偿后的滤波能够较好地估计系统,可以减少传感器测量值丢失对滤波器性能的影响,增加估计的准确性。In engineering applications,wireless network control systems are mostly nonlinear systems.Due to long-distance transmission and unreliable communication networks,the measured values of system sensors may be lost in the transmission process,which influences accuracy estimation and system performance.In this study,the problem of unscented Kalman filtering for a class of nonlinear discrete stochastic systems affected by correlated noise and sensor measurement loss is studied.By introducing a random variable that obeys Bernoulli distribution and has known conditional probability to describe the random sensor measurement loss,an algorithm is proposed to compensate the data.The results are verified by standard numerical software.The results show that the filter compensated by the algorithm can estimate the system well,greatly reduce the impact of sensor measurement loss on the filter performance,and increase the accuracy of estimation.

关 键 词：无线网络控制系统 非线性离散系统 状态估计 无迹卡尔曼滤波 丢包 系统协方差 估计误差 系统噪声 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]