Chapter
Jun 29, 2020
13th Asia Pacific Transportation Development Conference

A Simulation of the TDOA Chan Localization Used in the Train Station and Indoor Location System

Publication: Resilience and Sustainable Transportation Systems

ABSTRACT

This dissertation studies the mathematics behind “A Simple and Efficient Estimator for Hyperbolic Location” and sorts out the solution procedures of “An Approximately Efficient TDOA Localization Algorithm in Closed-Form for Locating Multiple Disjoint Sources with Erroneous Sensor Positions”. The former dissertation introduced a famous algorithm, the Chan method. It is used to solve TDOA localization in the train station and indoor location system. The latter paper provided an improved method based on the Chan. In this paper, the following works have been finished. (1) Detailed deductions of the Chan method have been provided, specially the missing procedures and some indigestible processes. Mathematical principles are also being given. (2) The core concepts of deducing the Chan method are provided. (3) The solution procedures of “An Approximately Efficient TDOA Localization Algorithm in Closed-Form for Locating Multiple Disjoint Sources with Erroneous Sensor Positions” have been straightened out and listed. The above works bring benefit to the development and propagation of TDOA.

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REFERENCES

Chan, Y. T., and Ho, K. C. (1994). “A simple and efficient estimator for hyperbolic location.” IEEE Transactions on Signal Processing, 42(8), 1905-1915.
Hahn, W., and Tretter, S. (1973). “Optimum processing for delay-vector estimation in passive signal arrays.” IEEE Transactions on Information Theory, 19(5), 608-614.
Yang, L., and Ho, K. C. (2009). “An approximately efficient tdoa localization algorithm in closed-form for locating multiple disjoint sources with erroneous sensor positions.” IEEE Transactions on Signal Processing, 57(12), 4598-4615.

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Go to Resilience and Sustainable Transportation Systems
Resilience and Sustainable Transportation Systems
Pages: 450 - 459
Editors: Fengxiang Qiao, Ph.D., Texas Southern University, Yong Bai, Ph.D., Marquette University, Pei-Sung Lin, Ph.D., University of South Florida, Steven I Jy Chien, Ph.D., New Jersey Institute of Technology, Yongping Zhang, Ph.D., California State Polytechnic University, and Lin Zhu, Ph.D., Shanghai University of Engineering Science
ISBN (Online): 978-0-7844-8290-2

History

Published online: Jun 29, 2020
Published in print: Jun 29, 2020

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School of Optical-Electrical and Computer Engineering, Univ. of Shanghai for Science and Technology, Yangpu District, Shanghai. E-mail: [email protected]

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