Paper
15 April 2010 Information-based awareness model and active sensing in sensor resource management
Author Affiliations +
Abstract
In this paper, we studied the performance metrics for evaluating Network-Centric Warfare (NCW) battlefield awareness. We developed a set of novel information awareness metrics to enable responsive situation assessment under mission-critical conditions. The awareness metrics model (AMM) reflects the global information values of event locations such as position, terrain information, dangerousness, survivability, cell difficulty, and mission importance. Based on the enhanced awareness model, we developed an in-network cooperative multi-sensor search and track (ICMS) algorithm by solving a unified optimization problem in which each cell is searched and all detected objects are tracked for at least a desired track-lifetime period. We utilize a track-lifetime surface metric to represent the spatial and temporal aspects of object movements over a region of interest that requires frequent sampling of the known and estimated object positions (track maintenance) as well as possible object arrivals (track initiation). To demonstrate the effectiveness of our approach, we implemented our ICMS algorithm in a numerical example and found that it is effective in the sense that most cells with high activity are well-searched.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Dan Shen, Zhi Tian, Genshe Chen, Khanh Pham, and Erik Blasch "Information-based awareness model and active sensing in sensor resource management", Proc. SPIE 7698, Signal and Data Processing of Small Targets 2010, 76980V (15 April 2010); https://doi.org/10.1117/12.849788
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Cited by 6 scholarly publications.
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KEYWORDS
Sensors

Active remote sensing

Sensor networks

Data processing

Active sensors

Data modeling

Algorithm development

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