关键词: 非线性估计, 无味变换, 无味卡尔曼滤波, 扩展卡尔曼滤波, 粒子滤波, 统计线性回归

Abstract: This paper presents an in-depth survey on the Unscented Transformation（UT） and the Unscented Kalman Filtering（UKF） algorithm，including the origination of the nonlinear estimation，the framework and the basic algorithm of UT，various evolutions of UT，the design guideline of sigma-point set，the basic algorithm of UKF and its variants，the further insight into UT，the comparison between UT and several other nonlinear derivative-free filtering methods，the application areas pertinent to UT and UKF，and a simulation example based on several typical forms of UKF.In the last part of the paper，some still unresolved problems about UT and UKF are exposed and an outlook of its future developments is explicitly listed too.Above all，some newest achievements and opinions are included in this paper，which are based on the author’s own research findings.

Key words: nonlinear estimation, Unscented Transformation（UT）, Unscented Kalman Filtering（UKF）, extended Kalman filtering, particle filtering, statistical linear regression