BETA LACTAM INHIBITOR OF PILUS BIOGENESIS

Not Available The proposed research seeks to design a superior Autonomous Target Acquisition (ATA) algorithm by combining the best features of ladar-based and MMW-based (active/passive) ATA systems. We hope to overcome specific limitations of each system by incorporating complementary information from the other system. The thrust of our approach will be to determine specific regions of the sensors' mutual operational space where opportunities exist for synergistic fusion. Rather than first specifying a fusion approach and then testing it on various imagery, we will first analyze imagery to determine situations where detection rates can be increased and/or false alarm rates decreased by combining information from both sensors. For each such situation, we will test various promising fusion approaches and rank their effects on detection and false alarm rates using only imagery that is representative for the given situation. Finally, to automate the switching of fusion approaches, we will design a situation-adaptive expert system that determines when the missile enters a given situation based on sensed contextual information and on-board exogenous data sources. All sensor fusion approaches require co-registered imagery, but real-world sensors are frequently misaligned. We propose a highly robust, computationally efficient image registration solution based on the Quadrature Disambiguation algorithm.