Tracking an asynchronous sensor with Kaiman filters

In this paper, Kaiman filters (KFs) without and with nonlinear constraints are proposed to track an asynchronous sensor node with the help of synchronous anchors. A linear model is derived from time-of-arrival (TOA) measurements, and used to design the KFs. Hence, the proposed KFs do not have the modeling errors compared to the extended Kaiman filter (EKF), which employs the first-order Taylor approximation to linearize the nonlinear model. Furthermore, taking nonlinear constraints into account further improves the tracking performance of the KF. Simulation results indicate the superior performance of the proposed approach.