Incremental collaborative trajectory estimation using WSN based on multifrontal QR factorization

Wireless Sensor Networks (WSN) are used for a variety of applications, including the target's trajectory estimation. Most proposed solutions are based on sequential estimation. However, in this paper we present a new solution to the trajectory estimation problem using the batch estimation approach. In our solution, we model the problem as a system of equations AX = b, with matrix A being sparse and vector X being the trajectory. Next, through multifrontal QR factorization, factorization A = QR is distributed between the sensors, which calculate it collaboratively and incrementally. Simulation results show that our solution has the same performance as the centralized estimator. Also, we demonstrate its implementation viability by showing that the processing and memory requirements are compatible to generic motes characteristics.