IEMEK Journal of Embedded Systems and Applications (대한임베디드공학회논문지)

Institute of Embedded Engineering of Korea (대한임베디드공학회)
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Learning-based Improvement of CFAR Algorithm for Increasing Node-level Event Detection Performance in Acoustic Sensor Networks

음향 센서 네트워크에서의 노드 레벨 이벤트 탐지 성능향상을 위한 학습 기반 CFAR 알고리즘 개선

  • Received : 2020.08.25
  • Accepted : 2020.09.22
  • Published : 2020.10.31
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Abstract

Event detection in wireless sensor networks is a key requirement in many applications. Acoustic sensors are one of the most frequently used sensors for event detection in sensor networks, but they are sensitive and difficult to handle because they vary greatly depending on the environment and target characteristics of the sensor field. In this paper, we propose a learning-based improvement of CFAR algorithm for increasing node-level event detection performance in acoustic sensor networks, and verify the effectiveness of the designed algorithm by comparing and evaluating the event detection performance with other algorithms. Our experimental results demonstrate the superiority of the proposed algorithm by increasing the detection accuracy by more than 45.16% by significantly reducing false positives by 7.97 times while slightly increasing the false negative compared to the existing algorithm.

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References

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