Distributed target tracking by time of arrival and received signal strength with unknown path loss exponent

The problem of distributed target tracking using time of arrival and received signal strength with unknown path loss exponent (PLE) is studied. The PLE is modelled as a Markov chain with three states and an adaptive gridding strategy is adopted to adjust the PLE recursively in a bounded interval. Therefore, the target tracking model is formulated as a jump Markov non-linear system. The interacting multiple model () estimator is applied to derive the target state estimates for each sensor and the covariance intersection approach is used to fuse sensor-based estimates in a distributed fashion. Simulation results show a promising performance for the proposed filter.