Application research on vector coherent frequency‐domain batch adaptive line enhancement in deep water

The low frequency line spectrum noise radiated by ships has strong stability and is difficult to eliminate, which is the key information required for passive signal detection. A vector coherent frequency‐domain batch adaptive line enhancement method is proposed to address the issue of insufficient d...

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Veröffentlicht in:IET radar, sonar & navigation sonar & navigation, 2024-10, Vol.18 (10), p.1859-1873
Hauptverfasser: Li, He, Wang, Tong, Guo, Xinyi, Su, Lin, Mo, Yaxiao
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Sprache:eng
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Zusammenfassung:The low frequency line spectrum noise radiated by ships has strong stability and is difficult to eliminate, which is the key information required for passive signal detection. A vector coherent frequency‐domain batch adaptive line enhancement method is proposed to address the issue of insufficient detection capability of traditional scalar adaptive line enhancement (ALE) algorithms for ship characteristic line spectra in complex deep‐sea environments. This method not only introduces the idea of frequency‐domain batch processing, but also uses synchronously collected sound pressure and particle velocity as dual input, fully utilising the coherence characteristics between vector channels to output high gain line spectrum signals and improve computational efficiency. In simulation and sea trial data validation, compared with the time‐domain vector coherent adaptive line enhancement algorithm, this method has shorter time consumption, higher efficiency, and can improve the detection ability of line spectrum signals under low signal‐to‐noise ratio conditions. The bearing estimation results output by this algorithm is also more accurate. The authors propose a method of vector coherent frequency‐domain batch adaptive line enhancement. The method takes the sound pressure and particle velocity signals collected by the vector hydrophone as dual input. Compared with time‐domain methods, this method has higher computational efficiency and better line spectrum detection ability.
ISSN:1751-8784
1751-8792
DOI:10.1049/rsn2.12621