To track multiple ships and estimate the feature parameters of multiple emitters on board using electronic intelligence satellites under clutter interference, a long and random revisit time, and other complex conditions, a novel tracking algorithm using both kinematic (position and velocity) and feature information based on an improved Multiple Hypothesis Tracking (MHT) approach is proposed in this paper. Firstly, the characteristics of multi-ship tracking with multiple emitters using satellite electronic information are analysed, and a new model of an emitter is built as an extended target in geographical coordinates. Secondly, a pre-processing of measurements is utilised via hierarchical clustering using the location and feature information of emitters. Thirdly, feature information is incorporated into the MHT framework using Jensen-Shannon divergence distance and fuzzy C-means clustering to calculate track scores. Finally, we present the prediction and update of target states, especially the update of feature parameters, to realise joint kinematic and feature tracking of ships. The results of the simulation show that the proposed method has much better tracking performance than the standard MHT algorithm.