The report discusses target recognition based on kinematic data. A model for aerial-mission recognition is presented. The missions, which are characterized by different motion patterns, are fight, attack, reconnaissance, transport and general aviation. The model is based on the theory of Hidden Markov Models (HMM). It has been implemented in the Data Fusion node (DF). DF consists of models and algorithms for the different steps of the data fusion process, i. e. collection and analysis of data, situation assessment, threat analysis and adaptation/control. A purpose with DF is to investigate how to improve situation awareness for a platform operator. Target recognition makes possible an improvement in situation awareness. Simulations of aerial-mission recognition are presented. Another model for target recognition based on kinematic data is shortly presented. It is based on Dempster-Shafers´ rule. Finally some general aspects on target recognition based on kinematic data are discussed. Such aspects are for example how the target recognition can be used within a network of platforms and how it can be used as a base for sensor management.