[1] Ke Wei, Wu Lenan, Yin Kuixi, et al. Wireless location algorithm using digital broadcasting signalsbased on neural network [J]. Journal of Southeast University (English Edition), 2010, 26 (3): 394-398. [doi:10.3969/j.issn.1003-7985.2010.03.005]

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Wireless location algorithm using digital broadcasting signalsbased on neural network()

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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:

26

Issue:

2010 3

Page:

394-398

Research Field:

Information and Communication Engineering

Publishing date:

2010-09-30

Info

Title:

Wireless location algorithm using digital broadcasting signalsbased on neural network

Author(s):

Ke Wei¹;  2;  Wu Lenan ¹;  Yin Kuixi²

¹ School of Information Science and Engineering, Southeast University, Nanjing 210096, China
² School of Physics and Technology, Nanjing Normal University, Nanjing 210097, China

Keywords:

digital broadcasting signals;  neural network;  extended Kalman filter(EKF);  backwards error propagation algorithm;  multilayer perceptron

PACS:

TN911

DOI:

10.3969/j.issn.1003-7985.2010.03.005

Abstract:

In order to enhance the accuracy and reliability of wireless location under non-line-of-sight(NLOS)environments, a novel neural network(NN)location approach using the digital broadcasting signals is presented. By the learning ability of the NN and the closely approximate unknown function to any degree of desired accuracy, the input-output mapping relationship between coordinates and the measurement data of time of arrival(TOA)and time difference of arrival(TDOA)is established. A real-time learning algorithm based on the extended Kalman filter(EKF)is used to train the multilayer perceptron(MLP)network by treating the linkweights of a network as the states of the nonlinear dynamic system. Since the EKF-based learning algorithm approximately gives the minimum variance estimate of the linkweights, the convergence is improved in comparison with the backwards error propagation(BP)algorithm. Numerical results illustrate that the proposed algorithm can achieve enhanced accuracy, and the performance of the algorithm is better than that of the BP-based NN algorithm and the least squares(LS)algorithm in the NLOS environments. Moreover, this location method does not depend on a particular distribution of the NLOS error and does not need line-of-sight(LOS)or NLOS identification.

References:

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Memo

Memo:

Biographies: Ke Wei(1976—), male, graduate; Wu Lenan(corresponding author), male, doctor, professor, wuln@seu.edu.cn.
Foundation items: The National High Technology Research and Development Program of China(863 Program)(No.2008AA01Z227), the Cultivatable Fund of the Key Scientific and Technical Innovation Project of Ministry of Education of China(No.706028)
Citation: Ke Wei, Wu Lenan, Yin Kuixi. Wireless location algorithm using digital broadcasting signals based on neural network [J].Journal of Southeast University(English Edition), 2010, 26(3):394-398.

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