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

Lin Zhou1, Jiawei Wu1, Qian Wei1

  • 1School of Artificial Intelligence, Henan University, Zhengzhou 450046, China.

Entropy (Basel, Switzerland)
|September 23, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a novel multi-sensor scheduling method that reduces target threat and loss risks. The approach adaptively schedules sensors for accurate target tracking with minimal resources.

Keywords:
convex optimizationmulti-sensor schedulingmulti-step predictionrisk assessment

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Area of Science:

  • * Sensor systems engineering
  • * Cooperative detection systems
  • * Risk assessment and management

Background:

  • * Multi-sensor systems face risks from attacks and environmental uncertainties.
  • * Existing methods may not adequately address diverse risk factors in sensor scheduling.
  • * Target threat and loss risks require integrated assessment for effective detection.

Purpose of the Study:

  • * To propose a novel multi-sensor scheduling method based on joint risk assessment with variable weight.
  • * To develop a comprehensive joint risk model incorporating target threat and loss risks.
  • * To optimize sensor scheduling for improved rapidity and accuracy in multi-sensor cooperative detection.

Main Methods:

  • * Introduced a new scheme for target threat risk considering target state and expert experience.
  • * Constructed a joint risk model by combining target threat and target loss risks.
  • * Developed a variable-weighted joint risk assessment model and relaxed the non-convex optimization problem to a subconvex problem.

Main Results:

  • * The proposed method adaptively schedules sensors based on joint risk assessment.
  • * Achieved accurate target tracking using minimal sensor resources.
  • * Demonstrated improved rapidity and optimization in sensor scheduling solutions.

Conclusions:

  • * The developed multi-sensor scheduling method effectively mitigates target threat and loss risks.
  • * Adaptive weighting of risks enhances the robustness of sensor scheduling.
  • * The approach offers an efficient solution for cooperative detection systems requiring minimal resource utilization.