Mobile Tracking Based on Support Vector Regressors Ensemble and Game Theory
Author(s) -
Fanzi Zeng,
Shaoyuan Liu,
Renfa Li,
Zeng Qingguang
Publication year - 2014
Publication title -
international journal of distributed sensor networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.324
H-Index - 53
eISSN - 1550-1477
pISSN - 1550-1329
DOI - 10.1155/2014/403927
Subject(s) - non line of sight propagation , computer science , position (finance) , estimator , node (physics) , tracking (education) , noise (video) , support vector machine , artificial intelligence , algorithm , wireless , telecommunications , statistics , mathematics , psychology , pedagogy , image (mathematics) , structural engineering , finance , engineering , economics
A two-step tracking strategy is proposed to mitigate the adverse effect of non-line-of-sight (NLOS) propagation to the mobile node tracking. This strategy firstly uses support vector regressors ensemble (SVRM) to establish the mapping of node position to radio parameters by supervising learning. Then by modelling the noise as the adversary of position estimator, a game between position estimator and noise is constructed. After that the position estimation from SVRM is smoothed by game theory. Simulations show that the proposed strategy results in the more accurate performance, especially in the harsh environment.
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