A mobile system for non-centralized target tracking in presence of dynamic interferences

This paper focuses on the application of particle filtering to tracking a single target by a network of mobile agents using measurements affected by dynamic interferences. The proposed solution is of general value and can be applied to systems with limited resources, and constraints on sensing modes, power and bandwidth utilization, and algorithm complexity. The highlight of the method is on its ability to handle multiple unknown dynamic sources of interference by compensation, which does not require prior information about the number of interferers, their locations, mobilities and powers, and does not attempt direct estimation of the number of interferers and their parameters and dynamics. The solution relies on a model that introduces a bias in the measurement equation that accounts for the interference contributions. We provide simulation results which demonstrate the performance of the proposed system.