MDA seeks to maximize the utility of collected sensor data through a fusion architecture that provides an integrated view of the battlespace. IAVO proposes research and development of a fusion architecture, which employs novel algorithmic techniques using a foundation of sound stochastic theory, probabilistic inference methodologies and pattern recognition techniques to develop the iView2TM (Integrated Battlespace Viewing for Threat Discrimination and Sensor Fusion) solution which will: Use all data collected from multiple sensors through an intelligent fusion architecture to ensure all available data is married to detected objects in space, decrease data redundancy and focus on presenting the most relevant information for quick and accurate target assessments; Account for the uncertainty and disparity in gathered intelligence; Incorporate historical data from previously collected intelligence about threatening objects to make more informed decisions; Characterize object types and natures based on collected and derived intelligence, using the fusion architecture as the medium through which data is combined and viewed; Use trajectory information to create a back-tracking capability to determine threat origin and compare missile characteristics against known weapon technology and potential end-phase targets to provide support for countermeasure decision-making; Provide actionable intelligence for planning appropriate countermeasures.
Keywords: Integrated Battlespace View, Threat Discrimination, Sensor Fusion, Persistent Isr Capabilities, Adaptive Gaussian Filtering, Classification Of Airborne Objects, Signal Process
