Multi-Sensor Scheduling Method Based on Joint Risk Assessment with Variable Weight

Lin Zhou, Jiawei Wu, Qian Wei, Wentao Shi, Yong Jin

Research output: Contribution to journalArticlepeer-review

Abstract

In multi-sensor cooperative detection systems, to reduce target threat risk caused by attack tasks and target loss risk induced by uncertain environmental factors, this paper proposes a multi-sensor scheduling method based on joint risk assessment with variable weight. Firstly, considering the target state and prior expert experience of sensor scheduling, this paper gives a new scheme of target threat risk. Then, by combining the given target threat risk and the target loss risk, this paper constructs a joint risk model to meet the diversity of risk assessment. Secondly, a variable-weighted joint risk assessment model is given based on the adaptive weight of target loss risk and target threat risk, and the optimization problem of multi-sensor scheduling is described to minimize the multi-step prediction of the variable-weighted joint risk model. Finally, this paper relaxes above the non-convex optimization problem as a subconvex problem and designs the scheme of multi-sensor scheduling, improving the rapidity and optimization of the sensor scheduling solution. The simulation results show that the proposed method can adaptively schedule sensors and accurately track targets by using minimum sensor resources.

Original languageEnglish
Article number1315
JournalEntropy
Volume24
Issue number9
DOIs
StatePublished - Sep 2022

Keywords

  • convex optimization
  • multi-sensor scheduling
  • multi-step prediction
  • risk assessment

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