Measurement fusion using maximum-likelihood estimation of ballistic trajectories
A novel method is proposed for asynchronous measurement fusion using maximum-likelihood (ML) estimator. This method is applied to multiple radar tracking and reconstruction of ballistic trajectories. The performance and robustness of the ML measurement fusion technique are analysed using a generic simulation scenario involving multi-sensor weapon locating in urban environment. Accuracies of firing point and impact point estimation of mortar grenades and artillery rockets are also evaluated taking into account different radars’ characteristics and geometries of the scenario. Immunity to glint noise, limited time of observation, and uncertainty of ballistic coefficient are also investigated. This study shows the effectiveness of the new method, advantages over track fusion approach, and reveals its practical value.