The technical objectives of this effort are to develop low cost sensor packages optimized for three types of unmanned platforms: UGVs (unmanned Ground Vehicles), SUAVs (Small unmanned Aerial Vehicles), and UGS (Unatte...
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ISBN:
(纸本)0819444936
The technical objectives of this effort are to develop low cost sensor packages optimized for three types of unmanned platforms: UGVs (unmanned Ground Vehicles), SUAVs (Small unmanned Aerial Vehicles), and UGS (unattended Ground sensors). Additional goals are to develop robust (secure, jam resistant, stealthy) communications to network these sensor systems throughout complex terrain, develop command and control (C2) software tools to include mission planning, monitoring, dynamic re-planning, sensor planning and management functions;and to demonstrate a system-of-systems capability when fusing information from these various unmannedsensor systems. These capabilities provide the battlefield commander organic unmannedsensor network assets to complete his Battlespace Situational Awareness (BSA) picture for targeting, direct and indirect-fire weapons, and threat avoidance. The networked sensors will provide remote monitoring of areas of interest out to similar to10km not covered by higher echelon surveillance assets and without placing soldiers in harm's way, will increase unit areas of coverage (force multiplier), and will provide near real time BSA and targeting data for early warning to speed decision making and reaction time.
Despite improvements in both data compression and transmission technologies in recent years, video bandwidth constraints continue to limit performance of sensornetworks. Furthermore, prolonged mission lifetimes requi...
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ISBN:
(纸本)0819440914
Despite improvements in both data compression and transmission technologies in recent years, video bandwidth constraints continue to limit performance of sensornetworks. Furthermore, prolonged mission lifetimes require that sensor nodes operate with minimal power. Dynamically Reconfigurable Vision (DRV) seeks to collect only visual information that is relevant to the vision task(s) at hand, and thus to make more effective use of available bandwidth and computational resources than is possible with conventional imaging technology. This is achieved through the intelligent, dynamic allocation of spatial and temporal sensing resources in response to the dynamics of the scene itself. Minimization of irrelevant data in the video processing chain reduces processing requirements and allows communication of more information in real-time over bandwidth-limited channels. This leads to a reduction in sensor node power consumption, complexity, size, and cost. Last year, we presented the design of our prototype DRV camera, featuring a real-time reconfigurable CMOS imager and a fast ethernet interface. The DRV sensor array supports 3 overlapping, independently-configurable, time-correlated windows per frame. In its typical configuration, one window continuously detects new regions of interest within a wide FOV, while the other 2 windows operate concurrently as independent tracking windows: Tracking rates can exceed several hundred Hertz. Independent gain and offset control for each window permits contrast enhancement within a selectable localized region of the FOV. Here, we report on a prototype system developed around this camera, which includes simply a host laptop, power supply, and an ethernet cable. This camera is capable of operating under either manual control, or under the control of automatic target detection and tracking algorithms. Our roadmap for ongoing and future DRV development work is described, including the designs for a megapixel DRV camera with a true snapshot
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