The spherical simplex unscented transformation 论文
2004引用 335
Advanced Statistical Methods and ModelsStatistical and numerical algorithmsTarget Tracking and Data Fusion in Sensor Networks
详细信息
- 发表日期
- 2004-02-03
- 发表年份
- 2004
关键词
Advanced Statistical Methods and ModelsStatistical and numerical algorithmsTarget Tracking and Data Fusion in Sensor Networks
摘要
This paper describes a new and better-behaved sigma point selection strategy for the unscented transformation (UT). The UT approximates the result of applying a specified nonlinear transformation to a given mean and covariance estimate. The UT works by constructing a set of points, referred to as sigma points, which have the same known statistics as the given estimate. This paper describes a sigma point selection strategy that requires, for n dimensions, n+2 sigma points; and n+1 of these points lie on a hypersphere whose radius is proportional to /spl radic/n. The weights on each point are proportional to 1/n. We illustrate the algorithm through an example which uses simultaneous localisation and map building.