Abstract:

To improve the accuracy and real-time performance of the the Received Signal Strength Indica- tion (RSSI)-based location system,an estimation algorithm based on adaptive scaled Unscented Kalman Filter (UKF) is proposed. By analyzing the RSSI location model, this new algorithm convents the loca- tion problem into estimation of nonlinear system model. It can estimate the target position and the RSSI channel attenuation parameter simultaneously by using the scaled symmetric sampling and the modified Sage-Husa noise statistic estimaters. The experimental and simulation results show that, compared with standard UKF, the proposed algorithm can effectively reduce the state estimation error, improve the filter stability and provide more better accuracy for target location.

Key words: information processing, wireless sensor network, location, adative filtering, unscented Kal- man filter