Target Detection in Passive Sonar with Stochastic Classifier and Adaptive Threshold

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Komari Alaei Hamed; FARSI HASSAN

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Journal Paper

Paper Information

Journal: ELECTRONIC INDUSTRIES Year:2018 | Volume:8 | Issue:4 Page(s): 33-48

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Information Journal Paper

Title

Target Detection in Passive Sonar with Stochastic Classifier and Adaptive Threshold

Author(s)

Komari Alaei Hamed | FARSI HASSAN | Issue Writer Certificate

Keywords

Passive SonarQ1

k-meanQ1

Bayesian ClassifierQ1

Adaptive ThresholdQ1

Target DetectionQ1

Particle FilterQ1

Monte CarloQ1

Abstract

Sounds detection in the water is one of the main challenges of researchers in the sonar field. This challenge will become more complex when the depth of the sea is low or published sound is negligible. Usually Target Detection in sonar system is performed with a fix defined threshold that it will increase the detection error. The purpose of this paper is to present a new Target Detection method in Passive Sonar using Adaptive Threshold. In the proposed method, Adaptive Threshold due to the statistical analysis and Bayesian Classifier applied in both time and frequency domains. Particle Filter is used to calculate prior pdf in Bayesian Classifier. Finally Target Detection point is calculated after fusion detection points in time and frequency domains by adaptive filter. The results indicate that the proposed method has better performance (23%) than recent methods in Passive Sonar Target Detection issue.

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APA: Copy

Komari Alaei, Hamed, & FARSI, HASSAN. (2018). Target Detection in Passive Sonar with Stochastic Classifier and Adaptive Threshold. ELECTRONIC INDUSTRIES, 8(4 ), 33-48. SID. https://sid.ir/paper/229605/en

Vancouver: Copy

Komari Alaei Hamed, FARSI HASSAN. Target Detection in Passive Sonar with Stochastic Classifier and Adaptive Threshold. ELECTRONIC INDUSTRIES[Internet]. 2018;8(4 ):33-48. Available from: https://sid.ir/paper/229605/en

IEEE: Copy

Hamed Komari Alaei, and HASSAN FARSI, “Target Detection in Passive Sonar with Stochastic Classifier and Adaptive Threshold,” ELECTRONIC INDUSTRIES, vol. 8, no. 4 , pp. 33–48, 2018, [Online]. Available: https://sid.ir/paper/229605/en

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