Adaptive Threshold Selection for Collaborative Target Tracking
Authors
CHunxiang Liu, ZhiGang Liu
Corresponding Author
CHunxiang Liu
Available Online March 2017.
- DOI
- 10.2991/amcce-17.2017.60How to use a DOI?
- Keywords
- Wireless Sensor Networks, adaptive threshold selection, detection, tracking.
- Abstract
A uniform threshold is not reasonable as a faraway sensor can hardly get the same signal strength as that of a near one from the target. To cope with this problem, we give an adaptive threshold selection (ATS) algorithm, in which we construct the minimum error probability cost function based on the probability of false positive and false negative of sensor nodes, and calculate the optimal detection threshold to select the nodes that attend in target tracking. The simulation results show that the proposed algorithm improves the tracking accuracy while reducing the network energy consumption.
- Copyright
- © 2017, 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 - CONF AU - CHunxiang Liu AU - ZhiGang Liu PY - 2017/03 DA - 2017/03 TI - Adaptive Threshold Selection for Collaborative Target Tracking BT - Proceedings of the 2017 2nd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 2017) PB - Atlantis Press SP - 342 EP - 346 SN - 2352-5401 UR - https://doi.org/10.2991/amcce-17.2017.60 DO - 10.2991/amcce-17.2017.60 ID - Liu2017/03 ER -