Introduction

As the level of autonomy in cars increases, choosing the right number and type of sensors becomes more complex. Traditional sensing options are available, but over the years, the application of radar within the automotive industry has positively evolved the definition of safety and efficiency.

Because it can work in extreme environmental conditions such as rain, snow, dust and bright sunlight and also provide precise distance and velocity information, radar is considered the most appropriate sensing modality to meet New Car Assessment Program (NCAP) requirements. Vehicle architectures are increasingly relying on smart radar sensors, with all processing occurring at the edge to send object lists to central electronic control units.

Radar sensing has become a cost-efficient sensing modality for required advanced driver assistance system (ADAS) functions and to meet Society for Automotive Engineers vehicle autonomy levels 2+ and even 3+, as shown in Figure 1. Radar technology is evolving to support higher levels of automated driving, with high levels of range and resolution for precise detection and decision. And because radar sensors can now support multiple functions, the use of space around the vehicle becomes more manageable. As the numbers of sensors increase, the space around the car becomes constrained. Due to multimodal functionally of the sensors, engineers are eventually able reduce the number of sensors.

Up to level 3+, vision and radar sensing modalities can cost efficiently address the requirements, while for level 4 and beyond, all three sensing modalities – including lidar – might be necessary (as shown in Table 1). Radar sensors, when built with cascaded transceivers (a higher number of virtual channels), offer lidar-like performance (higher angular resolution), but at an optimized cost.

Radar technology alerts drivers to the possibility of a collision by providing a warning or taking necessary evasive action. The complexity of safely turning or changing lanes and navigating tight corners presents significant design challenges when working to advance vehicle autonomy, however. Visibility around corners has presented major technical barriers in designing high-quality ADAS and parking assistance, as well as affecting the broader adoption of autonomous vehicles worldwide. Being able to see farther and more clearly with radar devices leads to improved sensor fusion for safer automated driving and parking applications. In addition to the performance that radar brings to the table, the key advantage of using radar for ADAS is its ability to operate reliably regardless of weather conditions.

77- to 81-GHz millimeter-wave (mmWave) long-range radar sensors from TI offer the ability to detect objects in a wide geographical area and can cover a range of 200 m. Mid-range sensors operate in the range of 100 m to 150 m, while short-range sensors use transceivers, with signal-processing equipment mounted behind the bumper, to track an object or person 30 m to 50 m from the vehicle. Complementary metal-oxide-semiconductor technology has enabled a high level of integration in our front end, especially a single chip that integrates both analog and digital.