Design of blind distributed UFIR filter based on average consensus for WSNs

Abstract

Wireless sensor networks (WSNs) often operate under harsh conditions requiring robustness from the estimator. This paper develops a distributed unbiased finite impulse response (UFIR) filter based on average consensus as a more robust alternative to the Kalman filter (KF). Unlike the distributed KF, the distributed UFIR filter typically requires only one consensus filter and completely ignores the noise statistics and initial values. As an example, we consider a vehicle travelling along a circular trajectory under unpredictable impacts and errors in the noise statistics. Better performance of the UFIR filter is demonstrated under diverse operation conditions.