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Recurrent Algorithm for TDOA Localization in Sensor Networks

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.

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

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