The advanced trainer is cost-effective, saving time and expense |
Elbit Systems Ltd. was awarded an order by the Israeli Ministry of Defense (IMOD) for the supply of Armored Driving Trainers (ADTs) for several Israel Defense Forces combat vehicle types as well as for a Forward Observer Trainer (FOT) for surveillance and observation of Israel's borders. The order is in an amount which is not material to Elbit Systems.
Mounted on top a motion platform, Elbit Systems' Armored Driving Trainer (ADT) enables 6 degrees freedom of movement, specifically designed to provide trainees with a highly realistic driving experience. The system supports driver training in a wide range of combat and non-combat scenarios. The wide variety of scenarios it offers enables driver training in diverse weather and harsh field conditions, thus creating practice situations (such as driving under enemy fire or on dangerous slopes) that are not feasible to perform in the actual battlefield - even during field exercises . The advanced trainer is cost effective, saving time and expense while providing mobile, scalable and modular deployment, multi-platform type support, and a network-based and user friendly interface.
Elbit Systems' Forward Observer Trainer (FOT) was developed especially to suit the unique needs of border protection scenarios and is already in use, training new forward observers ("FOs"), while maintaining the operational readiness of those already in service. The FOT is a combat support and field intelligence trainer, designed to enable full simulation of real-life battlefield situations for FOs posted along all types of terrain, performing border control and protection. The scenarios offered by the FOT are actual real-life scenarios depicting the real borders to be observed in each of the FO's service. Interoperable with C4I and communication systems, the scenarios incorporated include fire planning, ranging and field operation as well as target detection, recognition, identification, acquisition and engagement in diverse environmental conditions, while using a wide variety of day and night sensors.