Radar in 7500 m Well Based on Channel Adaptive Algorithm
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| izdano v: | Sensors vol. 25, no. 19 (2025), p. 5994-6021 |
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| Glavni avtor: | |
| Drugi avtorji: | , , , , |
| Izdano: |
MDPI AG
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| Teme: | |
| Online dostop: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 022 | |a 1424-8220 | ||
| 024 | 7 | |a 10.3390/s25195994 |2 doi | |
| 035 | |a 3261088504 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 231630 |2 nlm | ||
| 100 | 1 | |a Liu Handing | |
| 245 | 1 | |a Radar in 7500 m Well Based on Channel Adaptive Algorithm | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Deep-well radar telemetry over ultra-long cables suffers from strong frequency-selective attenuation and impedance drift under high temperature and pressure. We have proposed a channel-adaptive “communication + acquisition” architecture for a 7500 m borehole radar system. The scheme integrates spread-spectrum time domain reflectometry (SSTDR; m-sequence with BPSK) to monitor the cable in situ, identify termination/cable impedance, and adaptively match the load, thereby reducing reflection-induced loss. On the receiving side, we combine time domain adaptive equalization—implemented as an LMS-driven FIR filter—with frequency domain OFDM equalization based on least-squares (LS) channel estimation, enabling constellation recovery and robust demodulation over the distorted channel. The full processing chain is realized in real time on a Xilinx Artix-7 (XC7A100T) FPGA with module-level reuse and pre-stored training sequences for efficient hardware scheduling. In a field deployment in the Shunbei area at 7500 m depth, radar results show high agreement with third-party geological logs: the GR-curve correlation reaches 0.92, the casing reflector at ~7250 m is clearly reproduced, and the key bottom depth error is 0.013%. These results verify that the proposed system maintains stable communication and accurate imaging in harsh deep-well environments while remaining compact and implementable on cost-effective hardware. | |
| 651 | 4 | |a China | |
| 653 | |a Cables | ||
| 653 | |a Spread spectrum | ||
| 653 | |a Localization | ||
| 653 | |a Communication | ||
| 653 | |a Data compression | ||
| 700 | 1 | |a Yang, Huanyu | |
| 700 | 1 | |a Bai Changjin | |
| 700 | 1 | |a Li, Siming | |
| 700 | 1 | |a Guo, Cheng | |
| 700 | 1 | |a Zhao, Qing | |
| 773 | 0 | |t Sensors |g vol. 25, no. 19 (2025), p. 5994-6021 | |
| 786 | 0 | |d ProQuest |t Health & Medical Collection | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3261088504/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3261088504/fulltextwithgraphics/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3261088504/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |