Weighted optimization-based distributed Kalman filter for nonlinear target tracking in collaborative sensor networks

The identification of the nonlinearity and coupling is crucial in nonlinear target tracking problem in collaborative sensor networks. According to the adaptive Kalman filtering (KF) method, the nonlinearity and coupling can be regarded as the model noise covariance, and estimated by minimizing the i...

Full description

Bibliographic Details

Main Authors:	Jie Chen, Jiahong Li, Shuang-Hua Yang, Fang Deng
Format:	Default Article
Published:	2016
Subjects:	Artificial intelligence not elsewhere classified Other information and computing sciences not elsewhere classified Collaborative sensor network (CSN) Distributed adaptive filter Optimization Target tracking Artificial Intelligence and Image Processing Information and Computing Sciences not elsewhere classified
Online Access:	https://hdl.handle.net/2134/27721
Tags:	Add Tag No Tags, Be the first to tag this record!