文件名称：Unscented Filtering and Nonlinear Estimation
文件大小：651KB
文件格式：PDF
更新时间：2021-09-21 04:45:33
卡尔曼滤波
The extended Kalman filter (EKF) is probably the most widely used estimation algorithm for nonlinear systems. However, more than 35 years of experience in the estimation community has shown that is difficult to implement, difficult to tune, and only reliable for systemsthatarealmostlinearonthetimescaleoftheupdates.Many of these difficulties arise from its use of linearization. To overcome thislimitation,theunscentedtransformation(UT)wasdevelopedas a method to propagate mean and covariance information through nonlineartransformations.Itismoreaccurate,easiertoimplement, andusesthe same order ofcalculationsas linearization. Thispaper reviews the motivation, development, use, and implications of the UT.