“Future Radar Technologies and Applications,” a Presentation from IDTechEx
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The document discusses advancements in radar technologies, particularly focusing on automotive applications, including performance requirements and future trends such as 4-dimensional imaging. It highlights the importance of improved resolution, dynamic range, and power consumption in enhancing radar capabilities for autonomous driving. The report also explores how radar data can aid in object classification, emphasizing the role of 4D imaging radar in providing detailed information for better decision-making.
“Future Radar Technologies and Applications,” a Presentation from IDTechEx
- 1. Future Radar Technologies and Applications Dr. James Jeffs Senior Technology Analyst IDTechEx © 2024 IDTechEx
- 2. IDTechEx Provides Clarity on Technology Innovation Reports | Subscriptions | Consulting | Journals | Webinars Since 1999 IDTechEx has provided independent market research, consultancy and subscriptions on emerging technology to clients in over 80 countries. • Technology assessment • Technology scouting • Company profiling • Market sizing • Market forecasts • Strategic advice © 2024 IDTechEx 2
- 3. Agenda for Today’s Presentation 1. Radar and its use within different industries 2. Performance requirements for radar in automotive 3. Next generation radar performance and trends A. Increased resolution B. 4-dimensional detection C. High-dynamic range D. Cost E. Size F. Power consumption 4. How radar data can be used for classification Automotive Radar 2024-2044: Forecasts, Technologies, Applications www.IDTechEx.com/Radar Sample pages are available for all IDTechEx reports © 2024 IDTechEx 3
- 4. 4 © 2024 IDTechEx Radar and its Use Within Different Industries
- 5. Radar and cameras have very different capabilities. Radar • Provides range and relative velocity information • Very robust to poor lighting/poor visibility • Low resolution Performance Attributes of Radars Object classification Resolution Ranging Velocity Night Direct light Adverse weather Affordability Camera Radar © 2024 IDTechEx 5
- 6. Applications in Different Industries 6 © 2024 IDTechEx On-road Off-road Robotics and Other • ADAS features - adaptive cruise control • Safety features – blind spot detection, automatic emergency braking • Autonomous driving • In-cabin applications • Collision avoidance/blind spot detection • Autonomous operation • Autonomous robotics • Presence detection and people counting • Fill level monitoring • Traffic monitoring • Surveillance and security • Health care and vital sign monitoring
- 7. 7 © 2024 IDTechEx Performance Requirements for Radar in Automotive
- 8. Typical Applications for Automotive Radar Front monitoring • Automatic emergency braking • Adaptive cruise control Side monitoring • Blind spot detection • Junction automatic emergency braking © 2024 IDTechEx 8
- 9. Typical Applications for Automotive Radar Front monitoring – performance priorities • High resolution • Long detection range • Ranging & velocity measuring • Robust to all weather/lighting Side monitoring – performance priorities • Wide field of view • Range measuring • Cheap © 2024 IDTechEx 9
- 10. The Need for 4D Imaging Radar 4D imaging radars will be critical for enabling higher levels of autonomy. A primary example of this need is the car parked under an overpass scenario. A human can monitor this situation and override a false negative from an ADAS system. © 2024 IDTechEx 10
- 11. 11 © 2024 IDTechEx Next Generation Radar Performance and Trends
- 12. Angular resolution has been improving over the past decades. This is thanks to the introduction of 77 GHz and more channels in the radar. Perhaps more importantly, the resolution of radars in the elevation has been improving. Radar Trends: Angular Resolution (Lower is Better) 0.1 1 10 100 2005 2010 2015 2020 2025 2030 Angular Resolution Trends in Azimuth (˚) SRR MRR LRR 0.1 1 10 2016 2018 2020 2022 2024 2026 Angular Resolution Trends in Elevation (˚) SRR MRR LRR SRR, MRR, LRR = short range, medium range, long range Source: IDTechEx Research © 2024 IDTechEx 12
- 13. One of the enablers of better resolution has been increasing the number of transmitting and receiving channels on the radar. Virtual channels = No. transmitting channels X No. receiving channels. Virtual channels are like pixels on a camera – more is better, but that isn’t the full story. Radar Trends: Virtual Channel Count 1 10 100 1000 10000 2010 2012 2014 2016 2018 2020 2022 2024 2026 Trends in No. Virtual Channels SRR MRR LRR SRR, MRR, LRR = short range, medium range, long range Source: IDTechEx Research © 2024 IDTechEx 13
- 14. Improving resolution over the entire field of view. Here the radar range is 70m with an FOV of 80˚ or 250m with an FOV of 8˚. Its angular resolution is also dependent on where in the FOV the object is. Trading FOV with Range Image source: Nanoradar Figure is blurry. Can you improve it? © 2024 IDTechEx 14
- 15. 77 GHz radar and improved semiconductor technologies have led to a general reduction in the size of radar. High performance radars need larger antenna arrays, creating large footprints. - 5 10 15 20 - 100 200 300 400 500 600 700 800 2010 2012 2014 2016 2018 2020 2022 2024 2026 Area (1000 mm 2 ) Volume (1000mm 3 ) Radar Packaging Trends Volume Footprint Radar Trends: Volume and Footprint Source: IDTechEx Research Continental ARS540 Bosch FR5+ Arbe Lynx Arbe Phoenix 15
- 16. - 5 10 15 20 - 100 200 300 400 500 600 700 800 2010 2015 2020 2025 Area (1000 mm 2 ) Volume (1000mm 3 ) Radar Packaging Trends Volume Footprint Larger volumes and footprints can be justified by the increase in performance they allow. Radar Trends: Packaging and Performance Source: IDTechEx Research Outliers vanish as performance makes up for size. 0 1 2 3 4 5 - 20 40 60 80 100 120 2010 2015 2020 2025 Area (1000 mm 2 ) Volume (1000mm 3 ) Radar Packaging Trends Volume per Channel Footprint per Channel © 2024 IDTechEx 16
- 17. IDTechEx expects to see further divergence in sizing between high- performance radar and short-range radar. Diverging Radar Types Past Future Image Sources: IDTechEx Performance Compact size Present © 2024 IDTechEx 17
- 18. Power consumption correlates with performance. Most radars consume around 5 W, but high-performance radars are in the region of 20-25 W. Radar Power Consumption 0 5 10 15 20 25 2010 2012 2014 2016 2018 2020 2022 2024 2026 Power (W) Radar Power Consumption Image Sources: IDTechEx © 2024 IDTechEx 18
- 19. Dynamic Range – An Emerging Priority This is how we visualize dynamic range in cameras. Radars also have dynamic range, referring to the weakest and strongest reflections detectable. Camera phones - 10 stops/60dB Top end DSLR camera - 15 stops/90dB Best HDR automotive cameras - ~23.3 stops/140dB Human eye – 24 stops/144dB © 2024 IDTechEx 19
- 20. At CES 2024, Mobileye showed the performance from its upcoming radar product. One key factor that it had been working on from the outset was dynamic range. The image here shows Mobileye’s radar picking up a pallet at over 230m, near a highly reflective guard rail. Radars With High Dynamic Range - Mobileye Image Sources: Mobileye at CES, photo taken by IDTechEx analyst. © 2024 IDTechEx 20
- 21. Radar Price Ranges On-road Off-road Robotics and other $0 $10 $50 $100 $200 $500 $1,000 $5,000 High volume, low performance. Automotive SRR High volume, high performance. Automotive LRR High volume, emerging tech from start-up Medium volume emerging tech. Low volume emerging tech Very low volume emerging tech. 4D imaging radar for automotive © 2024 IDTechEx 21
- 22. 22 © 2024 IDTechEx How Radar Data Can Be Used for Classification
- 23. There is research in the area of using the RCS signature of different objects for classification. This started out for drone identification but also applies to traffic situations. Comparative Analysis of Radar Cross Section Based UAV Classification Techniques - Ezuma et al. – 2021 Classification With RCS 23 © 2024 IDTechEx
- 24. Other Radar Classification Techniques 24 © 2024 IDTechEx Source: Steradian Semiconductor Source: Arbe 4D imaging radar offer a range of benefits for classification. • RCS – likely material of object, metal vs organic • Resolution and range – physical sizing of object • Velocity – speed of object
- 25. 4D imaging radar offer a range of benefits for classification. • RCS – likely material of object, metal vs organic • Resolution and range – physical sizing of object • Velocity – speed of object Other Radar Classification Techniques 25 © 2024 IDTechEx Source: Steradian Semiconductor Source: Radar Transformer: An Object Classification Network Based on 4D MMW Imaging Radar, Bai et al. - 2021 Actual labels Model predictions Confusion matrix – radar-based classification
- 26. • Radar has a variety of applications, but automotive is the largest and most challenging. • Radar performance and technology has accelerated to meet the demands of autonomous driving. • 4D imaging radar provide rich data that can be combined with AI to enable accurate classification. Conclusions Automotive Radar 2024-2044: Forecasts, Technologies, Applications www.IDTechEx.com/Radar Sample pages are available for all IDTechEx reports © 2024 IDTechEx 26
- 27. Resources 27 © 2024 IDTechEx Key Radar Semiconductor Start-ups Uhnder https://www.uhnder.com/ Arbe https://arberobotics.com/ IDTechEx Market Research IDTechEx Automotive Radar 2024 – 2044: Forecasts, Technologies, Applications https://www.idtechex.com/radar Academic Research on Radar Classification Radar Object Classification Research, Bai et al., 2021 https://www.mdpi.com/1424- 8220/21/11/3854 Comparative Analysis of Radar Cross Section Based UAV Classification Techniques, Ezuma et al., 2021 https://arxiv.org/abs/2112.09774
- 29. 0 100 200 300 400 2005 2010 2015 2020 2025 2030 FOV Trends in Azimuth (˚) SRR MRR LRR 0 50 100 150 2005 2010 2015 2020 2025 2030 FOV Trends in Elevation (˚) SRR MRR LRR Radar field of view has been improving, particularly in elevation, as required by 4D radars. For automotive applications there is little benefit of going above 30-40° FOV in elevation. For other industries it could be useful. Radar Trends: Field of View SRR, MRR, LRR = short range, medium range, long range Source: IDTechEx Research © 2024 IDTechEx 29
- 30. Reducing Size – Antenna elements need to be close together which increases coupling - need to reduce emission power or fewer channels Increasing Power – High power increases coupling – need a larger antenna board or fewer channels Improving resolution – More channels means more antenna elements, which increases the radar’s footprint. Radar Trilemma Size Resolution Power © 2024 IDTechEx 30
- 31. Uhnder is also working on HDR radars. Mobileye concentrates on minimizing noise, hence being able to distinguish very low reflectivity objects from noise. Uhnder uses a novel emission encoding technique to improve dynamic range – Digital Code Modulation (DCM). Radars With High Dynamic Range - Uhnder © 2024 IDTechEx Image Sources: Uhnder 31
- 32. The formula for this is 𝐷 = 𝜎𝑚𝑎𝑥 𝜎𝑚𝑖𝑛 𝑅𝑚𝑎𝑥 4 𝑅𝑚𝑖𝑛 4 Where 𝜎 is the radar cross section (RCS) and 𝑅 is the range. Cars have an RCS of 100m2 Humans have an RCS of 0.1-1m2 If you have a car next to a human D = 1000 = 30dB. If you have a car at 10m and a human at 100m, D = 107 = 70dB. If you have a pickup (RCS=200) at 10m and a human at 200m, D = 3.2x108 = 85dB How Much Dynamic Range is Needed? © 2024 IDTechEx 32
- 33. Other Radar Classification Techniques 33 © 2024 IDTechEx Source: Steradian Semiconductor 4D imaging radar offer a range of benefits for classification. • RCS – likely material of object, metal vs organic • Resolution and range – physical sizing of object • Velocity – speed of object