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Abstract
A Risk-Based Sensor Management Method for Target Detection in the Presence of Suppressive Jamming
Highlights
Multi-sensor systems have played a major role in civil and military fields in recent years [1,2,3]
In order to obtain the optimal solution of objective function quickly, a decision tree search algorithm combining with branch and bound theory and greedy search is proposed
In order to illustrate the advancement of the branchand-bound-based greedy search algorithm (BB-GS), we compare it with three existing algorithms, namely uniform cost search (UCS), greedy search (GS) and branch-andbound-based standard cost search (BB-UCS) [29]
Summary
Multi-sensor systems have played a major role in civil and military fields in recent years [1,2,3]. The indicators of the first two methods have strict mathematical definitions, which make them unable to adapt to different needs [13] To solve these problems mentioned above, the risk-based management method has been proposed in [14]. The actual battlefield environment is considered in the modeling of the riskbased method In this way, the risk-based management method possessing practical value has become a research focus. The above literature merely considers the sensor's measurement risk of the target or the environment, while the radiation risk generated by the sensor is neglected To solve these problems mentioned above, a riskbased sensor management method for target detection in the presence of suppressive jamming is proposed in this paper.
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