A Reduced-Complexity Interacting Multiple Model Algorithm for Location Tracking in Heterogeneous Observation

DOI

10.2991/jrnal.2015.2.3.8How to use a DOI?

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 Atlantis Press.

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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TY  - JOUR
AU  - Xiaoyan Fu
AU  - Yuanyuan Shang
PY  - 2015
DA  - 2015/12/01
TI  - A Reduced-Complexity Interacting Multiple Model Algorithm for Location Tracking in Heterogeneous Observation
JO  - Journal of Robotics, Networking and Artificial Life
SP  - 173
EP  - 176
VL  - 2
IS  - 3
SN  - 2352-6386
UR  - https://doi.org/10.2991/jrnal.2015.2.3.8
DO  - 10.2991/jrnal.2015.2.3.8
ID  - Fu2015
ER  -