Autonomous driving relies on a variety of sensors, especially radars, which have unique robustness under heavy rain/fog/snow and poor light conditions. With the rapid increase of the amount of radars used on modern vehicles, where most radars operate in the same frequency band, the risk of radar interference becomes a compelling issue. This article analyzes automotive radar interference and proposes several new approaches that combine industrial and academic expertise toward the goal of achieving interference-free autonomous driving (AD).

An ultra-low power wake-up radio receiver using no oscillators is described. The radio utilizes an envelope detector followed by a baseband amplifier and is fabricated in a 130-nm complementary metal-oxide-semiconductor process. The receiver is preceded by a passive radio-frequency voltage transformer, also providing 50 Ω antenna matching, fabricated as transmission lines on the FR4 chip carrier. A sensitivity of -47 dBm with 200 kb/s on-off keying modulation is measured at a current consumption of 2.3 μ A from a 1 V supply. No trimming is used. The receiver accepts a -13 dBm continuous wave blocking signal, or modulated blockers 6 dB below the sensitivity limit, with no loss of sensitivity.

With the advent of Internet of Things (IoT) it has become clear that radio-frequency (RF) designers have to be aware of power constraints, e.g., in the design of simplistic ultra-low power receivers often used as wake-up radios (WuRs). The objective of this work, one of the first systematic studies of power bounds for RF-systems, is to provide an overview and intuitive feel for how power consumption and sensitivity relates for low-power receivers. This was done by setting up basic circuit schematics for different radio receiver architectures to find analytical expressions for their output signal-to-noise ratio including power consumption, bandwidth, sensitivity, and carrier frequency. The analytical expressions and optimizations of the circuits give us relations between dc-energy-per-bit and receiver sensitivity, which can be compared to recent published low-power receivers. The parameter set used in the analysis is meant to reflect typical values for an integrated 90 nm complementary metal-oxide-semiconductor fabrication processes, and typical small sized RF lumped components.

Background: The purpose of this study was to determine if 3D printed lenses with wavelength specific anti-reflective (AR) surface structures would improve beam intensity and thus radar efficiency for a Printed Circuit Board (PCB)-based 60 GHz radar. This would have potential for improved low-cost radar lenses for the consumer product market. Methods: A hyperbolic lens was designed in 3D Computer Aided Design (CAD) software and was then modified with a wavelength specified AR structure. Electromagnetic computer simulation was performed on both the ‘smooth’ and ‘AR structure’ lenses and compared to actual 60 GHz radar measurements of 3D printed polylactic acid (PLA) lenses. Results: The simulation results showed an increase of 10% in signal intensity of the AR structure lens over the smooth lens. Actual measurement showed an 8% increase in signal of the AR structure lens over the smooth lens. Conclusions: Low cost and readily available Fused Filament Fabrication (FFF) 3D printing has been shown to be capable of printing an AR structure coated hyperbolic lens for millimeter wavelength radar applications. These 3D Printed AR structure lenses are effective in improving radar measurements over non-AR structure lenses.

Perception and sensing of the surrounding environment are crucial for ensuring the safety of autonomous driving systems. A key issue is securing sensor reliability from sensors mounted on the vehicle and obtaining accurate raw data. Surface contamination in front of a sensor typically occurs due to adverse weather conditions or particulate matter on the road, which can degrade system reliability depending on sensor placement and surrounding bodywork geometry. Moreover, the moisture content of dust contaminants can cause surface adherence, making it more likely to persist on a vertical sensor surface compared to moisture only. In this work, a 76–81 GHz radar sensor, a 72–82 GHz automotive radome tester, a 60–90 GHz vector network analyzer system, and a 76–81 GHz radar target simulator setup were used in combination with a representative polypropylene plate that was purposefully contaminated with a varying range of water and ISO standard dust combinations; this was used to determine any signal attenuation and subsequent impact on target detection. The results show that the water content in dust contaminants significantly affects radar signal transmission and object detection performance, with higher water content levels causing increased signal attenuation, impacting detection capability across all tested scenarios.