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Sensor Management Method of Giving Priority to Confirmed Identified Targets.

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  • 1School of Information Science and Engineering, Southeast University, Nanjing 210096, China.

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Summary

This study introduces a new sensor management method for faster target identification. By prioritizing identifiable targets, it achieves comparable accuracy while significantly reducing confirmation time.

Keywords:
desired confidence levelentropyinformation theorysensor managementtarget identification

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Area of Science:

  • Artificial Intelligence
  • Information Theory
  • Sensor Systems

Background:

  • Traditional sensor management for target identification relies on information theory metrics like information gain.
  • These methods reduce overall uncertainty but neglect the speed of target confirmation.

Purpose of the Study:

  • To develop a sensor management method that accelerates target identification by prioritizing targets nearing confirmation.
  • To improve the accuracy of identification probability prediction in distributed Bayesian frameworks.

Main Methods:

  • Proposed an improved identification probability prediction method with global result feedback to local classifiers.
  • Developed a sensor management function using information entropy and expected confidence level to optimize identification uncertainty.
  • Modeled sensor management as an allocation problem with an objective function prioritizing identifiable targets.

Main Results:

  • The proposed method achieves correct identification rates comparable to existing information theory-based approaches.
  • Experimental results demonstrate the shortest average time to confirm target identification.

Conclusions:

  • The novel sensor management strategy effectively balances identification accuracy and speed.
  • Prioritizing targets with higher confidence levels enhances identification efficiency.