A robust location algorithm with biased extended Kalman filtering of TDOA data for wireless sensor networks

Many applications of wireless sensor networks (WSN) are based on self-positioning of sensor nodes. In this paper, an efficient robust location algorithm is proposed based on time measurement, requiring no global time synchronization in WSN and minimal extra hardware in sensor construction phase. We first utilize the TDOA measurements to locate target sensor node, then optimize the estimated values, which are educed from the algorithm as observed values for extended Kalman filtering and position estimation. It is shown the algorithm mentioned in the paper is close to CRLB (Cramer-Rao lower bound) for the static location estimator.