Fully Adaptive Active Sonar (FAAS)

The Metron team proposes to design, develop and demonstrate a prototype FAAS system. Our approach is specifically formulated to leverage innovative cognitive processing and inference algorithms to maximize information gain for a robust solution under changing environmental conditions. We propose a number of innovations to exploit non-traditional information to improve the discrimination power of the fundamental input data. A key objective of this effort is to formalize and make rigorous the mathematical process for active sonar cognition. We do this by providing a methodology that allows the system to express knowledge and understanding of phenomenology in a quantitative and analytic manner. This model is then used to evaluate alternative sonar and processing configurations. Support for alternative implementations is quantified in terms of the likelihood function and its role in formal measures of Information. Likelihood Functions provide the quantitative capture of the evidence, arising from data and parameters for each hypothesis, conditioned on information gathering. Information expressed in the likelihood function and posterior distributions of control hypotheses provide the formal mechanisms for direct feedback of the value of new information. This framework is then used to assess and recommend future implementations.