The Open Electrical & Electronic Engineering Journal

2016, 10 : 141-148
Published online 2016 November 21. DOI: 10.2174/1874129001610010141
Publisher ID: TOEEJ-10-141

RESEARCH ARTICLE
 A Novel Positioning Algorithm Based on Self-adaptive Algorithm of RBF Network

Jin Ren, * , Jingxing Chen and Liang Feng

* Address correspondence to this author at the School of Electronic and Information Engineering, North China University of Technology, No.5 Jinyuanzhuang Road, Beijing, P.R. China; Tel: 86 +13522323925; Fax: 86 +010-88803130; E-mail: rj@ncut.edu.cn

ABSTRACT

Much attention has been paid to Taylor series expansion (TSE) method these years, which has been extensively used for solving nonlinear equations for its good robustness and accuracy of positioning. A Taylor-series expansion location algorithm based on the RBF neural network (RBF-TSE) is proposed before to the performance of TSE highly depends on the initial estimation. In order to have more accurate and lower cost,a new Taylor-series expansion location algorithm based on Self-adaptive RBF neural network (SA-RBF-TSE) is proposed to estimate the initial value. The proposed algorithm is analysed and simulated with several other algorithms in this paper.

Keywords:

Angle-of-arrival (AOA), Assisted GPS (A-GPS), Position location, Self-adaptive RBF, Taylor series expansion, Time-difference-of-arrival (TDOA), Time-of-arrival(TOA).