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A multi-sensor-system cooperative scheduling method for ground-area detection and target tracking
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Yunpu ZHANG, Qiang FU, Ganlin SHAN. A multi-sensor-system cooperative scheduling method for ground-area detection and target tracking[J]. Frontiers of Information Technology & Electronic Engineering, 1998, -1(-1): .
@article{title="A multi-sensor-system cooperative scheduling method for ground-area detection and target tracking",
author="Yunpu ZHANG, Qiang FU, Ganlin SHAN",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="-1",
number="-1",
pages="",
year="1998",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2200121"
}
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%T A multi-sensor-system cooperative scheduling method for ground-area detection and target tracking
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%A Qiang FU
%A Ganlin SHAN
%J Journal of Zhejiang University SCIENCE C
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%I Zhejiang University Press & Springer
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A1 - Ganlin SHAN
J0 - Journal of Zhejiang University Science C
VL - -1
IS - -1
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%@ 2095-9184
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.2200121
Abstract: A multi-sensor-system cooperative scheduling method for multi-task collaboration is proposed in this paper. We studied the method for application in ground-area detection and target tracking. The aim of sensor scheduling is to select the optimal sensors to achieve the assigned combat tasks and obtain the best combat benefits. First, an area-detection model was built, and the calculation method of detection risk was proposed to quantify the detection benefits in scheduling. Then, combining the information on road constraints and the doppler blind zone, a ground-target tracking model was established, in which the posterior Carmér-Rao lower bound was applied to evaluate future tracking accuracy. Finally, an objective function was developed which considers the requirements of detection, tracking, and energy-consumption control. By solving the objective function, the optimal sensor-scheduling scheme can be obtained. The simulation results show that the proposed sensor-scheduling method can select suitable sensors to achieve the required combat tasks, as well as offering good performance in terms of area detection, target tracking, and energy-consumption control.
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