Data fusion in a multistatic radar network using covariance intersection and particle filtering

In this paper, centralized data fusion in multistatic radar networks with the capability of measuring bistatic range and range rate is analyzed. A new data fusion scheme comprising covariance intersection algorithm and particle filtering has been proposed. Performance of the proposed algorithm has been investigated via simulations and compared with the most commonly used SIR particle filter. Simulation results have shown that with the proposed approach target state estimation could be carried out more accurately than conventional SIR particle filter in terms of RMS error. Particularly, estimation of the target location in Z axis has been achieved with acceptable accuracy while SIR particle filter could not manage to track target in Z axis at all.