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.