A water pollution source localization method in three-dimensional space using sensor networks

Most existing water pollution source localization methods via sensor networks focus on two-dimensional pollution source. In this paper a three-dimensional water pollution source localization problem is discussed, and the spatial-temporal Unscented Kalman Filter(UKF) based on concentration samples in time and space is applied to solve the problem. In the simulation part, the performances of the spatial-temporal UKF and the temporal UKF are compared. The simulation results show that the localization based on spatial-temporal UKF performs better and has a higher stability, although the localization results of the methods are affected by the number of sensor nodes.