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Interference Mitigation for Multistatic Active Sonar

delete2015-07-01
delete6
PRE
AI
J
Jason M. Aughenbaugh *
B
Brian R. La Cour
J
James M. Gelb
DOI:10.1109/JOE.2014.2332951delete
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Abstract

Abstract

En 中文
Two methods for detecting and classifying mutual interference between sources in multistatic active sonar systems are developed and compared for frequency-modulated transmissions. Both methods compare the output of matched-filtered time-series data using two different waveform replicas: the intended transmit replica and a hypothesized interferer replica. The first method compares the absolute magnitudes of the two outputs, whereas the second method compares the local shape of the magnitude of the outputs to idealized replica correlations using an L-5-norm. Simulated examples indicate that the two methods are both effective, but with different tradeoffs. The magnitude-based method often performs better when the interference is relatively strong, and the shape-based method often performs better when the interference is weaker, and thereby harder to detect. It is also shown that excising the detected interfering direct blast at the beamformer output level effectively reduces clutter on displays and removes false contacts due to the interferer. The approach also shows potential for improving multistatic detection across platforms.
Keywords:
Interferer detection
mutual interference
noise excision
sonar
AI Summary

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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

IEEE Journal of Oceanic Engineering cover
IEEE Journal of Oceanic Engineering
IF:
5.3
Papers:
2.6K
Citations:
7.4K

Organization

U
university of texas system
Scholars:
18.5W
Papers: 15.6W
Citations: 210