Distributed Position Estimation of a Mobile Object Under a WSN Using a Robust UFIR Filter with Consensus on Estimates

Position estimation of a moving object benefits from using wireless sensor networks (WSN) technology, as each node can provide redundant and independent information about the state dynamics of the object. On the other hand, low cost and limited energy sensors are affected by external factors such as electromagnetic interference, weather, damaged sensors, and landscape itself, which man cause unstable data transmission resulting in missing and corrupted data. To overcome this drawback, robust estimators are required. In this paper, we develop a robust distributed unbiased finite impulse response filter (dUFIR) to solve the position estimation problem with consensus on estimates and under unstable data. It is shown that the robust dUFIR filter is suitable for position estimation of a mobile object, offering robust estimates under missing and corrupted data.