Spatiotemporal Registration for Multi-sensor Fusion Systems

被引：0
|
作者：
Bu, Shi-zhe [1 ]
Zhou, Gong-jian [1 ]
机构：
[1] Harbin Inst Technol, Res Inst Elect Engn, Harbin 150001, Peoples R China
来源：
INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND COMPUTER SCIENCE (AICS 2016) | 2016年
基金：
中国国家自然科学基金;
关键词：
Spatiotemporal registration; Data fusion; Unscented Kalman filter (UKF); State augmentation method;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A method of online sensor fusion with spatially and temporally misaligned sensors is considered in this paper. A spatiotemporal registration mode is developed for sensor alignment, and augment the target state vector with spatiotemporal bias. An unscented Kalman filter (UKF) is used to fuse and register these sensors, then the target state estimation as well as the spatial and temporal bias estimation can be obtained simultaneously. Simulations show that the proposed algorithm not only can align these sensors properly with both spatial and temporal bias, but can also obtain accurate fused tracks.
引用
收藏
页码：333 / 339
页数：7
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