Integrated Millimeter-Wave Radar Sensors: from Operating Principles to Applications

Topics:

• integrated radars,
• circuits and systems,
• signal processing algorithms

Summary:

Integrated millimeter-wave radar sensors which can detect object’s distance, relative velocity and angle with respect to the sensor itself are an emerging technology trend. Contrary to many other kinds of sensors which usually produce electrical value proportional to the measured quantity, information on range, speed and position are deeply masked inside radars’ output signal and require relatively high degree of processing intelligence to be extracted. Full stack radar development incorporates almost all electrical and electronics engineering disciplines from antenna design, over analog and digital circuits, up to algorithms and signal processing. Even though using electromagnetic waves for ranging is almost a century old concept, only recently with the appearance of first single-chip radars on the market radars are pretending to become dominant across many application areas. Radars have some of the unique advantages over the competing technologies that include being inherently robust to harsh environmental conditions like fog, glare, rain and snow. Besides low price, this fact plays the key role in today’s safety systems in automotive industry. This tutorial gives an overview of integrated millimeter-wave radar sensor operating principles with an accent on frequency-modulated continuous-wave (FMCW) radars, as well as design concepts and paradigms from circuit & system perspective.

Motivation:

Applications of portable short-range contactless radar sensors which provide simultaneous information on the presence, position and relative radial velocity are virtually countless. These radar systems not only have the potential to improve the service quality in numerous existing fields, but are also expected to be the driving force for many novel use-cases in the near future. Historically, millimeter-wave radar sensors were built from discrete components and therefore reserved only for low-volume markets. However, recent availability of a single-chip integrated solution with a low unit cost and small form factor, often referred to as the radar-on-chip (RoC), is becoming pervasive in a variety of areas.

Even though multiple competing sensing technologies exist, mm-wave radio frequency radars attract considerable attention thanks to their robustness against bad weather conditions and harsh environments. Automotive industry has been the trigger for the initial launch of integrated radar sensor products and to this day remains the major force driving the further development. Radar sensors that operate in the mm-wave band are going to be one of the key enabling technologies behind the autonomous vehicles. Radars are not only going to be used in future self-driving cars with the highest level of autonomy, but are also a fundamental part of present-day advanced driving assistance system (ADAS), in-cabin monitoring, parking and dead-angle sensors, etc.

Two fundamentally different microwave ranging methods, a pulse-based and continuous-wave (CW), coexist. The former ones are simply inefficient for monolithic integration, as they inherently suffer from higher peak(-to-average) power. Unmodulated CW radars can only determine the relative target velocity through the Doppler shift. Nevertheless, if the appropriate kind of carrier modulation (phase or frequency) is employed, object distances can also be resolved.

This tutorial aims to give a comprehensive introduction to modern integrated radar sensors. It would start from operating principles and explains how typical frequency and phase modulated radar sensors detect object’s range and velocity. Further it builds upon phased array radars to describe angle estimation in multiple-input multiple-output (MIMO) radars and imaging radar systems.

Crucial system-level parameters like range, velocity and angular resolution are identified and fundamental relationships and trade-offs are presented. Furthermore, the most popular circuit topologies inside the radio frequency front end of both, the frequency-modulated continuous-wave (FMCW) and the phase-modulated continuous-wave (PMCW), radars would be examined. Dominant design challenges, i.e., the highly linear frequency synthesizer in FMCW and very fast analog-to-digital data converters in PMCW radar front ends, are identified. Pros and cons of each topology, together with the influence of circuit-level parameters on system performance is going to be elaborated. Impact of technology choice (CMOS vs BiCMOS) on radar topology shall also be considered.

After analog front-end and mm-wave transceiver matters, common digital signal processing back-ends are discussed. In contemporary high-performance real-time radar systems, low-level point cloud is obtained either on a dedicated digital signal processor or radar signal processing accelerators. Only the higher-level detection algorithms are implemented in software. Typically, these domain-specific engines perform fast Fourier transform (FFT), constant false alarm rate (CFAR) detection, and similar functions that demand low latency, high data throughput, and fully streaming processing, mandatory for real time operation.

Finally, some of the advanced radar topics will be covered. These include future trends towards digitally-intensive and fully digital OFDM radars. Then, employing compressed sensing techniques in the spatial domain which enable subsampling below the Nyquist paved the path for emerging sparse antenna arrays. Furthermore, high resolution radars, such as imaging radars that feature sub-degree azimuth resolution thus starting to compete with conventional lidars will be mentioned. At the end, the talk will give a glance on application of machine learning and deep learning algorithms in modern radars and the use cases of artificial-intelligence-assisted radar signal processing will be brought up. Before concluding the tutorial an overview on some mainstream commercially available radar chips and solutions will be given and compared.

Presenter:

prof. Vladimir Milovanović,
University of Kragujevac, Serbia

Target Audience:

This topic is timely and aligns perfectly with the target audience of IEEE EUROCON. While many researchers work on machine learning for communication and networking within the context of 6G, few have expertise in RL, especially in MARL. A tutorial dedicated to providing basic knowledge on RL and MARL, covering theory to applications within the specific domain of communication networks, along with insights into advanced technologies, would make a significant contribution to the attendees. The EUROCON audience, concerned with wireless transmissions and networks, can learn how to approach RL and MARL frameworks in the context of wireless communication for 6G.

Given the nature of the tutorial, the intended audience is diverse, encompassing individuals with varying levels of expertise in wireless communications, artificial intelligence, and networking. The audience may include. 1) Individuals involved in research or academic study in the fields of AI, MARL, wireless communications, and specifically the MAC layer. 2) Professionals working in the telecommunications industry, particularly those focused on developing and implementing MAC layer protocols for next-generation wireless networks. 3) Professionals interested in exploring cutting-edge techniques and applications in 6G technology, including how RL and MARL can optimize MAC layer performance. The expected # of attendees is between ten and twenty.

Outline of Tutorial:

• Introduction and radar operating principles (approx. 45 min.)
  • Pulsed vs. Continuous-Wave (CW) radars with integration emphasis
  • Frequency-Modulated (FM) vs Phase-Modulated (PM) CW radars
  • range, velocity (Doppler) and angle estimation in MIMO radars
• Analog/RF radar front-end design topics (approx. 30-45 min.)
  • mm-wave FMCW synthesizers and circuit topologies for CW radars
  • CMOS/BiCMOS transceivers for FMCW and PMCW/OFDM radars
• Digital architectures for real-time processing (approx. 45 min.)
  • Spectral analysis of radar signals and 1/2-D hardware FFT processors
  • Constant False Alarm Rate (CFAR) detectors and radar trackers
  • Other radar signal processing accelerators and HW/SW codesign
• Higher-level Radar Algorithms and Applications (30-45 minutes)
  • Advanced topics: digital (OFDM) radars, compressed radar sensing
  • High-resolution imaging radars, sparse linear antenna arrays, etc.
  • Machine and Deep Learning in radar processing; Trends & conclusion

Disclaimer:

The final tutorial schedule, individual topic duration, and ordering are subject to change prior to the event, once the exact number of attendees in the audience is known..