Adaptive Clutter Suppression Algorithm
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Through adaptive algorithms, we can effectively suppress sea clutter, thereby enhancing data accuracy. This technique can be validated by comparing amplitude levels before and after suppression, typically implemented using signal processing methods like Recursive Least Squares (RLS) or Least Mean Squares (LMS) algorithms. Such implementations often involve real-time coefficient adjustment in digital filters to minimize clutter energy while preserving target signals. This approach enables better interpretation of underwater acoustic signals and more precise analysis of sonar data, which holds significant importance for marine research and underwater resource exploration. Key functions may include covariance matrix estimation, adaptive filter weight updates, and signal-to-clutter ratio optimization.
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