Radar for Fully Autonomous Driving

✍ Scribed by Matt Markel

• Publisher: Artech House Publishers
• Year: 2022
• Tongue: English
• Leaves: 339
• Category: Library

✦ Synopsis

This is the first book to bring together the increasingly complex radar automotive technologies and tools being explored and utilized in the development of fully autonomous vehicles - technologies and tools now understood to be an essential need for the field to fully mature. The book presents state-of-the-art knowledge as shared by the best and brightest experts working in the automotive radar industry today -- leaders who have "been there and done that." Each chapter is written as a standalone master class with the authors, seeing the topic through their eyes and experiences. Where beneficial, the chapters reference one another but can otherwise be read in any order desired, making the book an excellent go-to reference for a particular topic or review you need to understand. You'll get a big-picture tour of the key radar needs for fully autonomous vehicles, and grasp the complications and challenges that need to be addressed, including weather impacts, integration and safety issues, and RFI interference as the number of vehicles with radars continues to grow. This is an essential reference for engineers currently in the autonomous vehicle arena and/or working in automotive radar development, as well as engineers and leaders in adjacent radar fields needing to stay abreast of the rapid developments in this exciting and dynamic field of research and development.

✦ Table of Contents

Radar for Fully Autonomous Driving
Contents
Part I:
Radar Technologies for
Autonomous Vehicles
Chapter 1 Modern Radar Sensors in Advanced Automotive Architectures
1.1 Inspiration for More Advanced Systems
1.1.1 Traffic Density and Fatal Accident Rate
1.1.2 Human Factor
1.1.3 Autonomous Driving Levels
1.2 The Evolving Automotive Radar Landscape
1.3 Fast Chirp Sequence Radar Sensing
1.4 RFCMOS Car Radar Transceiver
1.5 Elements of a Radar Module
1.6 Angular Resolution Increase: MIMO Example and Cascaded Application
1.7 Vehicle Network and Compute Considerations
1.7.1 Vehicle Network Architecture Evolution
1.7.2 Distributed Versus Centralized Processing
1.7.3 Conclusion
1.8 Summary
1.9 Acknowledgments
References
Chapter 2 Design Considerations for Automotive Radar
2.1 Radar Requirements
2.2 The Spectrum for Automotive Radar
2.3 Range (Distance) Required for Automotive Radar
2.4 Automotive Radar Installation
2.5 Automotive Radar Considerations for Scanning the FOV
2.6 Frequency Modulation Waveforms and the Radar Data Cube
2.7 Outputs from Automotive Radar
References
Chapter 3
Digital Code Modulation
3.1 Introduction
3.2 FCM Versus DCM Architecture
3.3 Basics of DCM Radar
3.3.1 Range Processing
3.3.2 Velocity Processing
3.3.3 Angle Processing
3.4 DCM Radar Attributes
3.4.1 High Contrast Distance: Matched Filter
3.4.2 High Contrast Resolution
3.4.3 CDM MIMO (Higher Power on Target)
3.4.4 Interference Robustness and Interference Mitigation
3.4.5 Cascading: Coherent and Quasi-coherent Sensors and Networks
3.4.6 Code Design
3.5 DCM Radar Implementation
References
Chapter 4
Automotive MIMO Radar
4.1 Virtual Array Synthesis via MIMO Radar
4.2  Waveform Orthogonality Strategies in Automotive MIMO Radar
4.2.1 Waveform Orthogonality via TDM
4.2.2 Waveform Orthogonality via DDM
4.2.3 Waveform Orthogonality via FDM
4.3 Angle Finding in Automotive MIMO Radar
4.3.1 High Resolution Angle Finding with ULA
4.3.2 High Resolution Angle Finding with SLA
4.4 High Resolution Imaging Radar for Autonomous Driving
4.4.1 Cascade of Multiple Radar Transceivers
4.4.2 Examples of Cascaded Imaging Radars
4.4.3 Design Challenges of Imaging Radar
4.5 Challenges in Automotive MIMO Radar
4.5.1 Angle Finding in the Presence of Multipath Reflections
4.5.2 Waveform Orthogonality in Automotive MIMO Radar
4.5.3 Efficient, High Resolution Angle Finding Algorithms Are Needed
References
Chapter 5
Synthetic Aperture Radar for
Automotive Applications
5.1 Introduction
5.1.1 Historical Background
5.1.2 Comparison to Traditional Radar Systems
5.1.3 SAR and Point Cloud Imaging Performance
5.1.4 Applications for Automotive Use
5.2 Mathematical Foundation
5.2.1 Key Assumptions
5.2.2 Signal Model
5.2.3 Slow Time
5.3 Building an Automotive SAR
5.3.1 Measuring Ego-Motion
5.3.2 SAR Image Formation
5.3.3 Coexistence with Point Cloud Pipeline
5.3.4 Elevation Information
5.4 Future Directions
5.4.1 Forward-Facing SAR
5.4.2 SAR for Moving Objects
5.4.3 Gapped SAR
5.5 Conclusion
References
Chapter 6 Radar Transceiver Technologies
6.1 Background and Introduction to Automotive Radar
6.2 Block Diagram Overview of an FMCW Radar Transceiver
6.3 Challenges with Deeply Scaled CMOS
6.4 Active Devices in CMOS
6.5 Passives in CMOS
6.6 Circuit Architectures Suitable for Advanced CMOS
6.6.1 The Transmit Power Amplifier
6.6.2 The TX Phase Shifter
6.7 The LO/FMCW Chirp Generator
6.8 The Receiver Signal Chain
6.8.1 RX Frontend
6.8.2 Radar RX Baseband
6.9 Summary
References
Part 2:
Challenges and Solutions for the Automotive Environment
Chapter 7 Radar Challenges from the Automotive Scene
7.1 Introduction
7.1.1 Range Swath
7.1.2 Imaging Dense Clutter
7.1.3 Simultaneous Transmit and Receive
7.2 Scene Dynamic Range
7.3 Ground Bounce (Unresolved Reflections)
7.4 Multipath (Resolved Reflections)
References
Chapter 8
Radar Interference
8.1 Introduction
8.2 Motivation and Definitions
8.3 Impacts and Manifestation
8.3.1 LFM/FMCW
8.3.2 PMCW Radar and Mixed Waveforms
8.4 RFI Mitigations
8.4.1 Mitigations Local to the Radar
8.4.2 Global Mitigations: Noncooperative Countermeasures
8.4.3 Global Mitigations: Cooperative Countermeasures
8.4.4 Global Mitigations: Regulations
8.5 Recommendations for the Future
8.5.1 Use Less Energy and Power
8.5.2 Report Confidence
8.5.3 Create a Useful Taxonomy for RFI Mitigation
References
Chapter 9
The Impacts of Water (Weather)
on Automotive Radar
9.1 Introduction
9.2 System Losses
9.2.1 Transmission Loss
9.2.2 Target Loss
9.2.3 Radome Loss
9.3 Array Performance
9.4 Backscattering Phenomenology
9.4.1 Rainfall Backscatter
9.4.2 Road Spray
9.5 Potential Mitigations
References
Part 3:
Integration and System Considerations
Chapter 10
Safety Considerations for Radar in
Fully Autonomous Vehicles
10.1 Introduction
10.2 What Is Safety?
10.3 Safety Standards
10.3.1 ISO 26262 and ISO 21448
10.3.2 Relationship to Existing Standards and Processes
10.4 Lessons from Industry
10.4.1 Emphasize Understanding over Following Checklists
10.4.2 Embrace Systems Engineering
10.4.3 Address Safety in the Most Appropriate Place
10.4.4 Improve Supplier/Customer Engagement
10.4.5 Recognize the Criticality of a High Quality Safety Manual
10.4.6 Beware the Many Pitfalls of Safety Analysis
10.4.7 Applying Safety to Emerging or Complex Technologies
10.5 Safety Concepts for Level 4 ADS and Implications for Radar
10.5.1 Safety Considerations on Multiple Sensor Modalities
10.5.2 Safety Considerations on Radar Data
10.5.3 Radar FuSa and SOTIF Roots Causes and Mitigations
10.5.4 Safety Considerations Due to Available Radar Technology
10.6 Safety Considerations for Verification and Validation
10.7 Conclusion
References
Chapter 11
Testing Automotive Radars
11.1 Introduction: Why Is Testing Necessary?
11.1.1 Verification and Validation of System Performance
11.1.2 Conformance to Legal Regulations and Industrial Standards
11.1.3 Safety Performance Assessment
11.2 Measurable Parameters: From Sensor Level to Vehicle Integration
11.2.1 Transmitter Tests
11.2.2 Receiver Test
11.2.3 Antenna and Radome Test
11.2.4 Performance and Functional Tests
11.2.5 Integration Testing
11.3 Test Equipment
11.3.1 General Test Equipment
11.3.2 Radar Echo Generators
11.3.3 Measurement Antennas
11.3.4 Anochic Chambers
11.3.5 Positioners
11.4 Example Test Setups
11.4.1 Transmitter Test Setup
11.4.2 Setup for Sensor Calibration and Performance Tests
11.4.3 Setups for EMC and OOB Testing
11.4.4 Simulating Interference from Other Automotive Radar Transmitters
11.4.5 Exemplary Test Scenario
11.4.6 ADAS Integration Test Bed
11.4.7 ViL Test
References
List of Acronyms
About the Editor
About the Authors