Tracking of a rotating object in a Wireless Sensor Network using fuzzy based adaptive IMM filter

In this paper, a new fuzzy-logic based adaptive Interactive Multiple Model (IMM) filter is presented for tracking a vehicular rotating object in a Wireless Sensor Network (WSN). In this method, a Fuzzy-logic Inference System (FIS) is employed to adaptively tune the system noise covariance matrix associated with the Nearly Constant Velocity (NCV) model. By reducing the number of interacting models, our algorithm simplifies state-of-the-art IMM algorithms for tracking of a rotating object. Localization for data aggregation process is performed by means of the triangulation method in conjunction with dynamic grouping of sensors. Monte Carlo simulations show that this scheme achieves good tracking performance for both highly rotating and non-rotating objects compared to state-of-the-art IMM algorithms.