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On the Safe Road Toward Autonomous Driving: Phase noise monitoring in radar sensors for functional safety compliance

机译：关于自动驾驶的安全路法：功能安全合规性雷达传感器中的相位噪声监测

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The first approaches to improve vehicle safety were so-called passive safety systems, which did not directly interfere with the driving process but protected the occupants during a crash. In contrast, the first assistance system was the antilock braking system (ABS) successfully introduced in the early 1970s. This active system was developed to avoid an accident by automatically intervening in the braking behavior of the car. At about the same time, the first automotive radar prototype was presented. Since the invention of this very unwieldy radar system, organizations all around the world spent significant efforts in pushing the development of automotive radar systems forward. Today, radar sensors together with ultrasound sensors, lidar, and cameras form the backbone of advanced driver assistant systems (ADASs) as well as autonomous driving (AD), which is in the prototype stage. In particular, because of their robustness against adverse lighting and weather conditions, radar sensors are considered a key technology for modem vehicle safety and comfort systems. Along with the trend toward higher automation, more cars will be equipped with radar sensors in the near future. Because ADASs directly influence the vehicle dynamics, new regulating functional safety (FuSa) requirements, such as the ISO 26262 standard, were introduced. These requirements are mandatory to protect the road users.Modern automotive radar systems make use of the frequency-modulated continuous wave (FMCW) principle. Despite many advantages to pulse-based radars, one of the most limiting factors of an FMCW radar is the phase noise (PN) contained in the transmit (Tx) signal, which significantly affects the sensitivity and range. To fulfill the ISO 26262 standard, it is thus of high importance to monitor the PN of a radar system throughout its whole lifecycle. In this article, we present the most common PN measurement and estimation techniques for CW signals. Further, we address the problem of estimating the PN of an FMCW signal, which is of particular relevance for automotive FMCW radars and the aforementioned monitoring to fulfill the FuSa requirements. Finally, we present state-of-the-art methods for PN estimation and monitoring in automotive FMCW radar systems.
机译：提高车辆安全的第一种方法是所谓的被动安全系统，这与驾驶过程没有直接干扰驾驶过程，而是在碰撞过程中保护乘员。相比之下，第一辅助系统是在20世纪70年代初成功推出的防抱动系统（ABS）。开发了该活性系统以避免通过在汽车的制动行为中自动干预事故。在大约同时，提出了第一件汽车雷达原型。由于这一非常笨重的雷达系统的发明，世界各地的组织都在推动汽车雷达系统的发展方面的重大努力。如今，雷达传感器与超声传感器，激光器和相机一起形成高级驱动器辅助系统（ADASS）的骨干以及自动驾驶（AD），其在原型阶段。特别是，由于它们对不利照明和天气条件的鲁棒性，雷达传感器被认为是用于调制解调器安全性和舒适系统的关键技术。随着较高自动化的趋势，更多的汽车将在不久的将来配备雷达传感器。因为adass直接影响车辆动态，引入了新的调节功能安全（Fusa）要求，例如ISO 26262标准。这些要求是强制保护道路使用者的要求。现代汽车雷达系统利用频率调制的连续波（FMCW）原理。尽管对脉冲的雷达具有许多优点，但FMCW雷达的最限制因素之一是包含在发射（TX）信号中的相位噪声（PN），其显着影响灵敏度和范围。为了满足ISO 26262标准，因此高度重视在整个生命周期中监控雷达系统的PN。在本文中，我们为CW信号提供了最常见的PN测量和估计技术。此外，我们解决了估计FMCW信号的PN的问题，这对于汽车FMCW雷达以及满足FUSA要求的上述监测特别相关。最后，我们在汽车FMCW雷达系统中提出了最先进的PN估计和监控方法。

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  • 来源
    《IEEE Signal Processing Magazine》 |2019年第5期|60-70|共11页
  • 作者

    Gerstmair Michael; Melzer Alexander; Onic Alexander; Huemer Mario;

  • 作者单位

    Danube Integrated Circuits Engn GmbH & Co KG Infineon Technol Linz Austria|Johannes Kepler Univ Linz Inst Signal Proc Linz Austria;

    Infineon Technol Future Automot Radar Transceiver Monolith Microwa sceiver Monol Linz Austria|Max Integrated Austria Graz Austria;

    Danube Integrated Circuits Engn Gmbll & Co KG Infineon Technol Next Generat 77 GHz Automot Radar Monolith Microw Linz Austria;

    Johannes Kepler Univ Linz Inst Signal Proc Linz Austria;

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