Performance of State Estimation and Fusion with Elliptical Motion Constraints

被引:0
作者
Liu, Qiang [1 ]
Rao, Nageswara S., V [1 ]
机构
[1] Oak Ridge Natl Lab, Computat Sci & Engn Div, POB 2009, Oak Ridge, TN 37831 USA
来源
MULTISENSOR FUSION AND INTEGRATION IN THE WAKE OF BIG DATA, DEEP LEARNING AND CYBER PHYSICAL SYSTEM | 2018年 / 501卷
关键词
Long-haul sensor networks; State estimate fusion; Error covariance matrices; Nonlinear constraints; Elliptical track constraints; Root-mean-square-error (RMSE) performance; Projection;
D O I
10.1007/978-3-319-90509-9_3
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
We consider tracking of a target with known elliptical nonlinear constraints on its motion dynamics. The state estimates are generated by sensors and sent over long-haul links to a remote fusion center for fusion. We show that the constraints can be projected onto the ellipse and hence incorporated into the estimation and fusion process. In particular, two methods based on (i) direct connection to the center, and (ii) shortest distance to the ellipse are discussed. A tracking example is used to illustrate the tracking performance using projection-based methods with various fusers in a lossy long-haul tracking environment.
引用
收藏
页码:39 / 51
页数:13
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