Recurrent Algorithm for TDOA Localization in Sensor Networks

Authors

  • Igor Olegovych Tovkаch National Technical University of Ukraine «Kyiv Polytechnic Institute», Kyiv, Ukraine
  • Serhii Yakovych Zhuk National Technical University of Ukraine «Kyiv Polytechnic Institute», Kyiv, Ukraine

Keywords:

Passive location, , Time Difference of Arrival method, Extended Kalman Filter, Recurrent adaptive algorithm, Sensor network.

Abstract

Using the mathematical apparatus of the extended Kalman Filter, the recurrent algorithm of the passive location in sensor networks — based on the Time Difference of Arrival method in case of correlated errors of measurements — is developed. The initial estimates of Radio Frequency Sources coordinates and the correlation matrix of the vector estimation are determined based on the method of the least squares in case of 3 difference measurement distances. Efficiency analysis of recurrent adaptive algorithm and its comparison with the quadratic correction one are performed by statistical modeling. A comparison of them with the lower limit of the Cramer-Rao was carried out. The implementation of the recurrent adaptive algorithm requires 2.7 times less computational cost than the quadratic correction one.

Author Biographies

Igor Olegovych Tovkаch, National Technical University of Ukraine «Kyiv Polytechnic Institute», Kyiv, Ukraine

postgraduate

Serhii Yakovych Zhuk, National Technical University of Ukraine «Kyiv Polytechnic Institute», Kyiv, Ukraine

Ph.D., professor

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Published

2017-10-19

Issue

Vol. 9 No. 4 (2017): Oct./Dec. 2017

Section

Original Papers

License

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