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Self-Adaption Matched Filter and Bi-Directional Difference Method for Moving Target Detection.

Shitao Zhu1, Xiaoming Chen2, Xuehan Pan3

  • 1School of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China. shitaozhu@xjtu.edu.cn.

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Summary
This summary is machine-generated.

This study introduces a self-adaptive matched filter (SMF) and bi-directional difference method for detecting small moving targets in urban areas. The techniques enhance signal-to-interference-noise ratio (SINR) for reliable detection, even with single measurements.

Keywords:
linear frequency modulation (LFM) signallow signal-to-interference-noise ratio (SINR)self-adaption matched filtertarget detection

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Area of Science:

  • Radar Signal Processing
  • Target Detection
  • Urban Environment Sensing

Background:

  • Detecting small moving targets in complex urban environments presents significant challenges due to interference and noise.
  • Existing methods often struggle to achieve high detection probabilities with limited data.

Purpose of the Study:

  • To develop and validate a novel signal processing technique for robust small moving target detection in urban settings.
  • To improve the signal-to-interference-noise ratio (SINR) for enhanced target identification.

Main Methods:

  • A self-adaptive matched filter (SMF) was developed, incorporating a power factor derived from signal, echo, and noise properties.
  • Amplitude coherent accumulation was employed after SMF processing to boost SINR using multiple measurements.
  • A bi-directional difference technique was introduced to effectively differentiate target echoes from interference and noise.

Main Results:

  • The proposed SMF technique significantly improves the SINR by considering various signal and environmental factors.
  • Amplitude coherent accumulation further enhances SINR, leveraging information from multiple measurements.
  • The bi-directional difference method successfully distinguishes target echoes from clutter and noise.

Conclusions:

  • The combined SMF and bi-directional difference techniques enable high-probability detection of small moving targets in urban environments.
  • The method demonstrates effectiveness even with a single measurement, offering a significant advantage for real-time applications.