Automatic Target Recognition (ATR) constitutes a fundamental capability of Maritime Autonomous Vehicles, with corresponding services manifesting in a variety of forms, while relying on common core concepts - such as an overarching process and the main tasks forming it. Expanding beyond maritime contexts, such services find further application across different domains. For instance, radar systems serve both the classification of items in maritime environments and the identification of flying objects in air traffic control [1,2]. A Reference Model for ATR (ATR-RM) facilitates the communication of these core concepts, enabling diverse ATR applications to build upon it. Subsequently, solution models can be derived from the ATR-RM and knowledge acquired during that process can be reintegrated into the ATR-RM. Altogether, this fosters the cross-domain sharing of knowledge. In this chapter, we address the obtainment, maintenance, and application of such a reference model. First, we examine the domain of ATR in a generalized way in Section 7.1. Subsequently, we present our approach for obtaining and maintaining reference models in Section 7.2. Finally, we exemplarily demonstrate the result of applying our approach in Section 7.3.     «

Automatic Target Recognition (ATR) constitutes a fundamental capability of Maritime Autonomous Vehicles, with corresponding services manifesting in a variety of forms, while relying on common core concepts - such as an overarching process and the main tasks forming it. Expanding beyond maritime contexts, such services find further application across different domains. For instance, radar systems serve both the classification of items in maritime environments and the identification of flying obje...     »