Recurrent Algorithm for TDOA Localization in Sensor Networks

Igor Olegovych Tovkаch, Serhii Yakovych Zhuk


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.


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

Full Text:




  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.