A Reduced-Complexity Interacting Multiple Model Algorithm for Location Tracking in Heterogeneous Observation
- https://doi.org/10.2991/jrnal.2015.2.3.8How to use a DOI?
- data fusion, interacting multiple model algorithm, location tracking, wireless sensor networks.
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.
- © 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/).
Cite this article
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 - https://doi.org/10.2991/jrnal.2015.2.3.8 ID - Fu2015 ER -