The main objective of this SBIR is to advance the radar detection in near-shore environments of targets of interest, especially stealthy cruise missiles, amid the background clutter of birds, insects, weather and waves. FishEye Software will design and implement a Bayesian statistical classifier to categorize clutter types based on the optimal features that can be extracted from littoral environments. The first goal is to sort through large amounts of data, identifying the sources of clutter contained in it, and determining how well the distributions for different clutter types are separated in parameter space. Significant quantities of Raytheon data associated with the DD(X) program will be made available for FishEye Software to use, in addition to the Raytheon Synthetic Target Generator for simulating data. Identifying targets of interest amid such clutter is equally important and represents the Phase 1 option focus of this proposed effort.
Benefits: The ability to detect/discriminate targets of interest from various types of clutter is important in many radar applications such as air traffic control and threat detection. Improving this ability has significant benefits, particularly as more sophisticated cruise missiles are able to "hide" in clutter presented by the sea and other non-threatening sources such as migrating birds and swarming insects.
