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Optimally Integrate Automated Ship and Small Craft Classification Functions with the Maritime Tactical Picture Tools
Navy SBIR 2011.1 - Topic N111-030 NAVAIR - Mrs. Janet McGovern - [email protected] Opens: December 13, 2010 - Closes: January 12, 2011 N111-030 TITLE: Optimally Integrate Automated Ship and Small Craft Classification Functions with the Maritime Tactical Picture Tools TECHNOLOGY AREAS: Air Platform, Electronics, Battlespace ACQUISITION PROGRAM: PMA-290, Maritime Surveillance Aircraft Program Office OBJECTIVE: Develop innovative techniques to intelligently allocate sensor resources in order to maximize the utility of current radar maritime target classification tools with associated common maritime tactical picture processing tools. DESCRIPTION: The current state of the art in employing assisted target recognition for radar systems is to extract the maximum amount of target classification information using lower dwell-time radar modes prior to resorting to progressively more time consuming modes. For example, some target features may be discerned from a relatively low resolution search waveform, additional features may be identified from high range resolution (HRR) waveforms or from multiple HRR returns generated from different directions. If information from these returns does not identify sufficient features to confidently classify the target, more time consuming Inverse Synthetic-Aperture Radar (ISAR) imaging may be utilized. In certain instances ISAR and Electro Optical/Infrared (EO/IR) imaging may be done simultaneously to refine tracking of individual radar scatters on the target to support further refinement of the ISAR motion model to produce improved target dimension estimation and visual representation. In a separate effort to create a coherent and consistent surface track picture, NAVSEA has been developing a powerful toolset as part of the Ocean Surveillance Initiative (OSI). OSI provides precision geodetic alignment and registration of tracks along with Automatic Identification System (AIS)-to-radar track auto correlation as well as correlation with digital nautical chart information, the ability to associate EO/IR and ISAR Imagery automatically with radar tracks, a set of rudimentary ISAR classification tools, and automatic track generation. OSI is also able to adaptively configure the display to suit user needs using selectable filters, zoom in/out capability and ability to select and display imagery associated with a particular track of interest. The goal here is to optimally integrate OSI, or a comparable system, with automated radar based ship and small craft classification tools. This should be accomplished by intelligently resourcing the radar system to efficiently process targets in the radar field of view, perform real-time planning of flight tracks to optimally position the aircraft relative to targets, decide which modes are needed at what time to both maintain an up to date operational picture and classify targets, determine when sufficient feature extraction has occurred to perform classification, fuse feature data from multiple sources and times, and incorporate operator re-tasking. PHASE I: Perform a detailed analysis and determine the feasibility of the innovative technique to merge the automated ship and small craft classification functions with the maritime tactical picture tools. Develop an RDT&E plan addressing performance metrics, integration tasks and human-system interface. PHASE II: Design and demonstrate a prototype system in an operationally representative environment. PHASE III: Transition the developed technology to appropriate platforms and the fleet. PRIVATE SECTOR COMMERCIAL POTENTIAL/DUAL-USE APPLICATIONS: The general methods developed could be applicable to a wide range of functions ranging from behavioral analysis to multiple sensor fusion and homeland security to the DoD. REFERENCES: 2. Borden, B. & Cheney, M. (2002). Microlocal ISAR for Low Signal-to-Noise Environments http://www.rpi.edu/~cheney/papers/isarieee.pdf KEYWORDS: Inverse Synthetic Aperture Radar; Automatic Target Recognition; Ship and Small Craft Classification; Electro-Optic Sensor; Multi-Sensor; Common Maritime Operational Picture
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