Anchor Global Position Accuracy Enhancement Based on Data Fusion

The location information of sensor nodes in wireless sensor networks is crucial for various applications such as emergency rescue operations, environmental monitoring, home automation, and traffic control. In this paper, a new method to improve the anchor location accuracy in wireless sensor networks is proposed based on fusion of Global Positioning System (GPS) measurements and anchor-to-anchor parameter estimates. Novel algorithms are derived to increase the accuracy of anchor locations using both anchor-to-anchor distance and angle-of-arrival (AOA) estimates for both line-of-sight (LOS) and non-LOS (NLOS) scenarios. When using anchor-to-anchor distance estimates in LOS conditions, an optimization-based algorithm is developed. The Cramer-Rao lower bound (CRLB) is derived to benchmark positioning accuracy in 3-D environments with both GPS measurements and anchor-to-anchor parameter estimates, which has not been studied in the literature. Simulation results demonstrate that the proposed algorithms can substantially improve anchor position accuracy, and the performance of the proposed algorithms approaches the CRLB.