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Parallel Resonance01:23

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Microwave Photonics Systems Based on Whispering-gallery-mode Resonators
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Published on: August 5, 2013

Improved prewhitening method for linear frequency modulation reverberation using dechirping transformation.

Byung Woong Choi1, Eun Hyon Bae, Jeong Soo Kim

  • 1School of Electrical Engineering and Computer Science, Kyungpook National University, Daegu 701-702, Republic of Korea. bwng@ee.knu.ac.kr

The Journal of the Acoustical Society of America
|March 19, 2008
PubMed
Summary
This summary is machine-generated.

This study introduces an autoregressive prewhitener to improve target signal detection in linear frequency modulation reverberation. The method effectively removes unwanted LFM reverberation for clearer signal analysis.

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Area of Science:

  • Signal Processing
  • Radar Systems
  • Acoustic Signal Analysis

Background:

  • Linear frequency modulation (LFM) signals are common in radar and sonar.
  • LFM reverberation can obscure target signals, degrading system performance.
  • Existing methods for reverberation suppression may be complex or suboptimal.

Purpose of the Study:

  • To develop an effective autoregressive (AR) prewhitener for suppressing LFM reverberation.
  • To enhance the detection of target signals in the presence of LFM reverberation.
  • To provide a computationally efficient method for reverberation prewhitening.

Main Methods:

  • A dechirping transformation is applied to render LFM reverberation stationary within data blocks.
  • Autoregressive (AR) coefficients model the frequency response of stationary reverberation.
  • An inverse filter is constructed using AR coefficients to prewhiten the reverberation.

Main Results:

  • The proposed AR prewhitener successfully suppresses LFM reverberation.
  • Target signal enhancement is achieved by removing the LFM component.
  • The method demonstrates efficiency in prewhitening reverberation.

Conclusions:

  • The developed AR prewhitener is effective for enhancing target signals in LFM reverberation.
  • The dechirping and AR modeling approach provides a robust solution.
  • This technique offers a valuable tool for signal processing applications involving LFM signals.