A Sol-Gel Derived Barrier Layer for Larghe Area SiC Thyristor

Not Available Current object level change detection (OLCD) methods typically rely on performing differences between detected objects and objects stored in a database. Image Corp, Inc. proposes in this Phase I effort to develop a system dedicated to the joint exploitation of SAR and IR images that significantly improves the performance and application of existing OLCD through the incorporation of appropriate prediction, fusion, and temporal reasoning mechanisms. Algorithms will be developed to exploit predicted multi-sensor signatures, and data from multiple sensors will then be fused to eliminate false alarms that would be present in the single sensor scenario. Site model information and contextual evidence will be incorporated to quantify the confidence in the detection. Temporal trends will be computed using dynamic systems analysis and observer-predictor systems to evaluate the plausibility of a given detection. Temporal reasoning and the aggregation of evidence from multiple sensor observations will be carried out using a probabilistic approach supported by a Bayesian framework. We will emphasize a strict performance evaluation using both empirical as well as theoretical methods.