Adaptive Threshold Selection for Collaborative Target Tracking

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/).

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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  -