基于大规模MIMO雷达的炉料表面成像:毫米波集成电路如何实现高炉装料优化

Stefan Dipl.-Ing. Schuster, D. Zankl, S. Scheiblhofer, C. Feilmayr, J. Reisinger, R. Feger, A. Stelzer, C. Schmid
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引用次数: 3

摘要

在过去的十年中,集成毫米波集成电路设计取得了巨大的进步,主要针对自动驾驶[1],b[2]等移动应用。本文展示了这一进展如何与先进的信号处理和可用处理能力的巨大增加相结合,使完全不同的应用得以成功实现,但却引人注目。介绍了大规模多输入多输出成像雷达的设计演变,结合相关的实时信号处理和在线自动校准,用于分析高炉炉料表面,BLASTDAR系统。BLASTDAR系统目前已在奥钢联的所有五座高炉中运行了数年。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Massive MIMO Radar based Burden Surface Imaging: How mm-Wave Integrated Circuits Enable Optimization of Blast Furnace Charging
In the last decade there was enormous progress in integrated mm-wave integrated circuit design, targeting primarily mobility applications like automated driving [1], [2]. It is shown in this paper how this progress, paired with advanced signal processing and the enormous increase of available processing power, enables successful implementation of completely different, yet spectacular, applications. The evolution of designs of massive multiple-input multiple-output imaging radars in combination with the associated real-time signal processing and in-line autocalibration for analyzing the burden surface in blast furnaces, the BLASTDAR system, is presented. BLASTDAR systems now operate in all five voestalpine blast furnaces for several years.
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