From Innovation to Reality: The Impact of Radar Technology in Advancing Autonomous Vehicles

The automotive industry has shifted from human-driven vehicles to autonomous vehicles in the last few years. At present, manufacturers compete to bring the most advanced autonomous vehicles. In this pursuit, they focus on R&D in sensor technologies, including RADAR, Lidar, and others. These sensors offer power and precision in self-driving vehicles. Radar technology is commonly used to calculate the range, velocity, and an object’s angle on land, sea, and air. It plays a major role in the advanced driver assistance systems, an intermediate phase in self-driving vehicle development.

Microcontrollers in automotive radar systems

The broadband Frequency Modulated Continuous Wave radar has become the dominant technology for automotive use because it combines high resolution in range and depth perception, with the detection of objects like pedestrians and bicycles in a small radar cross-section. In an FMCW radar, both transmitter and receiver operate continuously; the transmitter deploys a sinusoidal carrier with a frequency that increases then decreases periodically over time- a sequence known as a chirp. The TX signal travels to the target object and is reflected back to the receiver; the difference in frequency between the RX and current TX signal is proportional to travel time, can be used to measure distance, and distinguish between different objects.

For example, the Aurix microcontroller is Infineon’s family of devices optimized for safety-critical automotive applications. The TC297TA, for example, includes a trio of 32-bit superscalar CPUs running at 300 MHz with eight MB Flash memory, DSP functionality, and multiple channels of both delta-sigma and SAR analog-to-digital conversion. The microcontroller runs under AUTOSAR, an industry-standard software architecture for automotive electronic control units. Infineon introduced XENSIV™ BGT60ATR24C, an automotive 60 GHz radar sensor in 2023. It enabled ultra-wide bandwidth FMCW operation in a small package. Sensor configuration and data acquisition are enabled with a digital interface and the integrated state machine enables independent data acquisition with power mode optimization for the lowest power consumption.

Texas Instruments launches new radar sensor chips for smarter, safer vehicles

In January 2024, Texas Instruments unveiled new semiconductors that can enhance auto safety and intelligence with the industry's first radar sensor chips for satellite radar architectures. The AWR2544 77GHz millimeter-wave radar sensor chip enhanced higher levels of autonomy by enhancing sensor fusion and decision-making in advanced driver assistance systems.

According to Fern Yoon, director of automotive systems at Texas Instruments, innovation in semiconductors as seen in such exhibits this year at CES, is driving progress in automotive systems while helping ensure safety for drivers on the road. He also added, that from more advanced driver assistance systems to smarter electric vehicle powertrain systems, TI is working alongside automakers to reimagine how reliable and intelligent technology can enable safer vehicles.

Combining radar, LIDAR, and visual sensors for enhanced detection

Compared to LIDAR and optical sensing technologies, radar is largely insensitive to environmental conditions like fog, rain, wind, darkness, or bright sun, but technical challenges remain. A radar system’s ability to detect an object largely depends on reflection strength. This is influenced by factors such as the object’s size, distance, absorption characteristics, reflection angle, and transmission power.

A vehicle or truck has a large reflection, but an ADAS-equipped vehicle must also account for pedestrians and motorcycles, which aren’t only smaller in size but have relatively few hard or metallic shapes to reflect radar signals. In a busy environment, the reflection from a truck can swamp that from a motorcycle; a small child standing next to a vehicle can become “invisible” to a radar receiver. Conversely, an object like a soda can produce a radar image far out of proportion to its size.

Increasing automation requires a system to analyze complex scenarios and correctly respond to multiple hazards. To meet these challenges, ADAS designers have combined the inputs from radar, LIDAR, ultrasonic, and visual sensors, to provide data individual sensors working independently cannot generate. Known as sensor fusion, this process combines the benefits of different sensors and measurement techniques in the most effective way possible to increase the reliability, range, and accuracy of overall results. Aggregated data then enables the software to form a detailed map of the vehicle‘s surroundings. The increase in demand for high-end passenger cars, the rise in concerns about vehicle & driver safety, and the implementation of safety regulations contribute toward the growth of the global radar market. According to Allied Market Research, the industry is expected to garner a revenue of $44.35 billion by 2028, with a CAGR of 4.7% between 2021 and 2028.

The shift toward 3D imaging

3D radar imaging provides a comprehensive, three-dimensional map of the place around the vehicle. The concept of motion-enhanced snapshots is introduced to generate larger apertures in the azimuth dimension. For the first time, 3-D imaging capabilities can be achieved with high angular resolution using a 1-D MIMO antenna array, which alleviates the requirement for large radar systems in autonomous vehicles. Improved spatial awareness provides accurate object detection and better decision-making capacities. It supports safer movement, especially where specific distance measurement is absolutely necessary. As a result, autonomous vehicles reliably execute tasks such as lane changing and obstacle avoidance, creating a smarter and more secure driving system.

MulticoreWare Inc. and Cipia have partnered on January 2, 2025. The collaboration aimed to display a cutting-edge demonstration of in-cabin monitoring sensor fusion at CES 2025. It fused 60GHz radar and IR camera technologies. Moreover, it combined their strengths to present exact tracking of driver and occupant vital signs, even in complicated conditions. MulticoreWare’s radar sensor data processing expertise has led to an efficient solution for identifying vital signs and detecting child presence.

The rapid evolution of sensor technologies, particularly radar, LIDAR, and visual sensors, is propelling the automotive industry toward safer and more intelligent vehicles. Integrating these technologies through sensor fusion enhances the accuracy and reliability of autonomous driving systems. In the coming years, self-driving vehicles will offer greater safety, efficiency, and smarter driving experiences. The continued advancement of these technologies is projected to redefine the next generation of vehicles with innovations like 3D radar imaging and collaborations between industry leaders.

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