Authors
Xiaoyan Fu, Yuanyuan Shang
Corresponding Author
Xiaoyan Fu
Available Online 1 December 2015.
DOI
https://doi.org/10.2991/jrnal.2015.2.3.8
Keywords
data fusion, interacting multiple model algorithm, location tracking, wireless
sensor networks.
Abstract
This paper is devoted to the problem of state estimate of discrete-time
stochastic systems. A low-complexity and high accuracy algorithm is presented
to reduce the computational load of the traditional interacting multiple
model algorithm with heterogeneous observations for location tracking.
By decoupling the x and y dimensions to simplify the implementation of
location, updated information is iteratively passed based on an adaptive
fusion decision. Simulations show that the algorithm is more computationally
attractive than existing multiple model methods.
Copyright
© 2013, the Authors. Published by ALife Robotics Corp. Ltd
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
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