Hyperbolic-weighted centroid Indoor Location Algorithm based on Kalman Filter

Abstract

The ultra-wideband(UWB) signal is affected by systematic measurement error and Not-Line-of-Sight(NLOS) error when it propagates in complex indoor environment, which leads to poor positioning accuracy and stability. In order to reduce the influence of error on the accuracy of positioning results, a Hyperbolic-weighted centroid algorithm based on Kalman Filter is proposed in this paper. The method is based on the time difference of arrival(TDOA) location model. The measured value of the TDOA distance difference is first filtered by Kalman Filter, and then the obtained results are used as the input of the Hyperbolic location algorithm to acquire the initial solution. For further offsetting the effect of error on positioning accuracy, a weighted centroid technique is applied. We evaluate the performance of the proposed method in both simulation and experimental results. The experimental results show that the position accuracy is effectively improved by the algorithm. When the measurement error satisfies the Gaussian distribution and the standard deviation is 0.1 m, the Root Mean Square Error(RMSE) of the location results is about 11 cm.