In the creation of a naval tactical environment that will meet today's rigorous standards for helicopter AntiSubmarine Warfare and Anti-Surface Warfare training, there are several technical issues that must be considered. This paper describes the elements comprising a complete and fully integrated naval environment as built to support a full flight tactical simulator facility engaged in mission training. These are discussed with a view to their engineering aspects as well as their integrated functionality within the environment.
The consideration of a complete electronic environment implies elements of both entity modeling and tactics modeling. Entity modeling includes platform representations (eg: dynamics and scoring), weapons representations (torpedoes, torpedo search patterns, anti-ship sea skimming missiles) and sensor representations (sonars, radars, radar complexes, and radar warning receivers). Tactics modeling involves capabilities such as maneuvers (screening, zigzags, searches), communications (Link 11 networks), identification criteria and emission control strategy.
Additional elements include the realistic representation of weather (moving frontal systems, wind layers and wind shear) and underwater acoustic environments (sound velocity profiles and propagation loss models).
Components are discussed with respect to their engineering facets, their user interfaces and their collective roles as integral parts of the complete environment. An example includes several elements of tactical maneuvering that implied the creation of customized interfaces and provide for critical capability in training. Another example is the modeling of platform sonars, and both active and passive sonobuoys, along with an acoustic representation and interfaces to create an underwater sensor capability that is both consistent from the user perspective and fully integrated with the rest of the tactical environment.
Key technical concerns experienced in the development and integration of the naval environment are explored. These include such trade-offs as model fidelity versus complexity, development costs, and ultimately, training value.