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The Rise of Radar for Autonomous Vehicles: Signal processing solutions and future research directions

机译：自治车辆雷达的兴起：信号处理解决方案和未来的研究方向

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摘要

Automotive radar is the most promising and fastest-growing civilian application of radar technology. Vehicular radars provide the key enabling technology for the autonomous driving revolution that will have a dramatic impact on everyone's day-to-day lives. They play a central role in the autonomous sensing suit because of the significant progress in the radio-frequency (RF) CMOS technology that enables high-level radar-on-chip integration and thus reduces the automotive radar cost to the level of consumer mass production. However, this would not be sufficient without high spatial resolution performance, which can be obtained by multiple-input, multiple-output (MIMO) and cognitive approaches at a lower cost.The uniqueness of automotive radar scenarios mandates the formulation and derivation of new signal processing approaches beyond classical military radar concepts. The reformulation of vehicular radar tasks, along with new performance requirements, provides an opportunity to develop innovative signal processing methods. In this article, we first revise conventional techniques for signal processing in automotive radar. Then, we emphasize the limitations of the historically driven conventional processing approaches in practical roadway scenarios and present alternative signal processing solutions. Finally, we propose several future research directions to enhance vehicular radar performance.
机译：汽车雷达是雷达技术的最有前途和最快的平民应用。车辆雷达为自主驾驶革命提供了关键支持技术，这将对每个人的日常生活产生巨大影响。它们在自主传感套装中发挥着核心作用，因为射频（RF）CMOS技术的显着进展，使得能够实现高级射线片集成，从而降低了消费者批量生产水平的汽车雷达成本。但是，如果没有高空间分辨率性能，这将不足以通过多输入，多输出（MIMO）和以较低的成本获得的认知方法获得。汽车雷达场景的唯一性要求新信号的配方和推导超出古典军事雷达概念的处理方法。车辆雷达任务的重新制定以及新的性能要求提供了开发创新信号处理方法的机会。在本文中，我们首先修改了汽车雷达中的信号处理的传统技术。然后，我们强调了历史上驱动的传统处理方法在实际道路场景中的局限性和目前的替代信号处理解决方案。最后，我们提出了几种未来的研究方向，以提高车辆雷达性能。

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  • 来源
    《IEEE Signal Processing Magazine》 |2019年第5期|20-31|共12页
  • 作者

    Bilik Igal; Longman Oren; Villeval Shahar; Tabrikian Joseph;

  • 作者单位

    Duke Univ Dept Elect & Comp Engn Durham NC USA|Univ Massachusetts Dept Elect & Comp Engn Dartmouth MA USA|Gen Motors GM Adv Tech Ctr Herzliyya Israel|GM Adv Tech Ctr Smart Sensing & Vis Grp Herzliyya Israel;

    Elbit Syst R&D Dept Radar & Elect Intelligence Syst Haifa Israel|Gen Motors Adv Tech Ctr R&D Radar Grp Herzliyya Israel;

    Gen Motors Adv Tech Ctr Herzliyya Israel;

    Ben Gurion Univ Negev Dept Elect & Comp Engn Beer Sheva Israel|Sch Elect & Comp Engn Beer Sheva Israel;

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