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June 10, 2026Remote SensingOpen Access

Extracting UAV Signatures from Sea Clutter: An Autocorrelation-Guided Cyclic Spectral Fusion Filtering Approach

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Authors

SLShuaiyong LinDNDing NieWJWangqiang Jiang

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Overview

Randomized trial demonstrates enhanced UAV signature extraction in complex marine environments, indicating improved detection capabilities.

Key Points

  • This research aims to develop a method for effectively extracting UAV signatures from sea clutter using cyclic spectral analysis.
  • Proposed an autocorrelation-guided cyclic spectral fusion filtering method.
  • Filtered out non-periodic components from echo signals to enhance target detection.
  • Compared performance against classic moving target indicator and singular value decomposition methods.
  • The proposed method significantly suppresses sea clutter, enhancing UAV target signals.
  • Achieved higher gain across various input signal-to-clutter-plus-noise ratios.
  • Demonstrated excellent detection performance compared to traditional approaches.

Cite This Study

Lin et al. (2026) studied this question.

synapsesocial.com/papers/6a28ff956f82f25be989c698https://doi.org/10.3390/rs18121896
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