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Related Experiment Video

Updated: Jan 15, 2026

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Radar in 7500 m Well Based on Channel Adaptive Algorithm.

Handing Liu1, Huanyu Yang1, Changjin Bai1

  • 1School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731,China.

Sensors (Basel, Switzerland)
|October 16, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces an adaptive deep-well radar system for stable communication and accurate imaging in harsh environments. The novel architecture ensures reliable data acquisition even with ultra-long cables under extreme conditions.

Keywords:
LMSOFDMSSTDRadaptive equalizationborehole radardeep-well telemetryleast-squares channel estimation

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Area of Science:

  • Geophysics
  • Electrical Engineering
  • Signal Processing

Background:

  • Deep-well radar telemetry faces challenges like frequency-selective attenuation and impedance drift.
  • Extreme temperatures and pressures in boreholes degrade signal quality over ultra-long cables.

Purpose of the Study:

  • To develop a channel-adaptive architecture for a 7500 m borehole radar system.
  • To ensure stable communication and accurate imaging in harsh deep-well environments.

Main Methods:

  • Integrated spread-spectrum time domain reflectometry (SSTDR) for in-situ cable monitoring and adaptive load matching.
  • Combined time and frequency domain adaptive equalization (LMS-driven FIR filter and LS-based OFDM equalization).
  • Real-time processing on a Xilinx Artix-7 FPGA for efficient hardware scheduling.

Main Results:

  • Achieved high agreement with third-party geological logs (GR-curve correlation of 0.92).
  • Clearly reproduced casing reflectors at ~7250 m depth.
  • Demonstrated a minimal key bottom depth error of 0.013%.

Conclusions:

  • The proposed system provides stable communication and accurate imaging in extreme deep-well conditions.
  • The compact and cost-effective FPGA implementation is suitable for practical deployment.
  • The channel-adaptive architecture effectively mitigates signal distortion in challenging environments.