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Related Concept Videos

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In structural analysis, singularity functions are crucial in simplifying the representation of shear forces in beams under discontinuous loading. These functions describe discontinuous  variations in shear force across a beam with varying loads by using a single mathematical expression, regardless of the complexity of the loading conditions. The singularity functions are derived from creating a free-body diagram of the beam and then making conceptual cuts at specific points to examine the...
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A Cognitive Paradigm to Investigate Interference in Working Memory by Distractions and Interruptions
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A Novel Interference Suppression Method for Interrupted Sampling Repeater Jamming Based on Singular Spectrum Entropy

Muyao Yu1, Shengbo Dong2, Xiangyu Duan3

  • 1Beijing Institute of Remote Sensing Equipment, Beijing 100854, China. yumuyao25s@163.com.

Sensors (Basel, Switzerland)
|January 6, 2019
PubMed
Summary

This study introduces a novel Singular Spectrum Entropy Function (SSEF) to suppress interrupted sampling repeater jamming (ISRJ). SSEF enhances target detection and peak-to-side-lobe ratio (PSR), especially in low signal-to-noise ratio (SNR) environments.

Keywords:
adaptive multi-scale segmentation (AMS)band-pass filteringinterference suppressioninterrupted sampling repeater jamming (ISRJ)singular spectrum entropy function (SSEF)

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Area of Science:

  • Radar signal processing
  • Electronic warfare
  • Information theory

Background:

  • Interrupted Sampling Repeater Jamming (ISRJ), a digital radio frequency memory (DRFM) based technique, generates multiple false targets.
  • Traditional interference suppression methods perform poorly against ISRJ at low signal-to-noise ratios (SNRs).

Purpose of the Study:

  • To propose a novel interference suppression method for ISRJ based on Singular Spectrum Entropy Function (SSEF).
  • To improve target detection probability and Peak-to-Side-Lobe Ratio (PSR) in low SNR conditions.

Main Methods:

  • Adaptive Multi-scale Segmentation (AMS) for signal processing.
  • Singular Value Decomposition (SVD) for singular spectrum extraction.
  • Shannon entropy-based Singular Spectrum Entropy Function (SSEF) for feature extraction and threshold detection.

Main Results:

  • The proposed SSEF method demonstrates improved performance compared to existing approaches.
  • Increased probability of target detection and enhanced PSR were observed.
  • The method shows stability against noise and jamming in low SNR conditions.

Conclusions:

  • SSEF is an effective method for suppressing ISRJ, particularly in challenging low SNR environments.
  • The approach offers a significant improvement in radar detection capabilities against sophisticated jamming techniques.