Multiple Use of Information from Force-on-Force Battle Training


Johan Jenvald,Magnus Morin


Force-on-force battle training is an established means of preparing military units for missions in crises and at war. To achieve realism in battle training, it is important that all major factors of the real battlefield are present in the training situation. Technical systems supporting force-on-force battle training typically focus on two issues: to provide a realistic, but non-lethal, battlefield and to perform data collection as a basis for after-action review. So far, these aspects of battle-training support systems have attracted significant interest, but considerably less attention has been paid to how the multitude of information generated during battle training is actually used.

In this paper, we explore how force-on-force battle training can provide valuable information in a number of contexts other than traditional after-action reviews. Accurate simulation and data collection during the training, together with careful filtering and analysis afterwards, increase our knowledge about the participating units abilities and shortcomings. Already at this stage, the knowledge is applicable for adaptation and development of tactics and equipment. Further refinement of the information forms a foundation for manual and automated modelling of DIS objects and command-post training.

For each of these cases, we investigate the requirements imposed on the simulation and data collection functions employed in the battle-training support system. As a reference system, we use the MIND system, which is an integrated simulation and data collection system for battle training with company-sized units.