Test & Evaluation Analytical Tools

The test and evaluation of weapon and aircraft control systems is vital to their success. Current weapon and aircraft control systems are software intensive and contain many complex interfaces. Testing these systems requires specialized equipment and personnel trained to operate the test equipment and analyze the data. The complexities of these systems make test and evaluation processes costly and prone to error. There are few automated systems and those that do exist still rely on the interpretation of data by system experts.

Over the past several years, SEA CORP has been developing a number of tools to aid in the test and evaluation process of complex systems. In general, these tools automate the identification of system requirements and the development and execution of test cases. They use computer-based “intelligent agents” to analyze test data and provide intelligent observations and recommendations. BLACKHAWK, SEAHAWK and IT-DAT are three such developmental testing tools.

BLACKHAWK

BLACKHAWK is designed to provide an inexpensive, modular, COTS-based tool for the collection and analysis of submarine Tomahawk missile data. BLACKHAWK can be seamlessly integrated into any of the submarine programs that include a Tomahawk Missile capability. It provides a real time method to validate the data being transferred between the submarine electronics and the Tomahawk missiles.

SEAHAWK

Building on the original BLACKHAWK design, SEA CORP developed an improved tool, “SEAHAWK” to integrate real-time navigation data into the Tomahawk testing process and to accommodate various simulation equipment.

IT-DAT (Intelligent Test Data Analysis Technology)

Based on research done in its SEAHAWK and BLACK HAWK Independent Research and Development (IRAD), SEA CORP recently won an SBIR contract to improve fidelity in the testing of complex systems. Aimed at major developmental programs, such as the Joint Strike Fighter, IT-DAT will use artificial intelligence to collect test data in several formats from various subsystems, compare and aggregate the various elements then interpret the data at a systems-level and generate results and recommendations.