mmWave Radar Sensor ModulesPrimary applications and market trends for mmWave radar

The main uses and applications of mmWave radar are as follows.

With the growing demand for enhanced automotive safety testing, the use of mmWave radar in systems that improve in-vehicle safety and exterior sensing technologies is attracting attention. Child Presence Detection (CPD) systems are primarily used as a measure to prevent heatstroke accidents by detecting children left behind in vehicles. Due to the challenges faced by camera-based monitoring in detecting people in blind spots created when they are covered by sheets or blankets, the high penetration of mmWave radar enables enhanced detection capabilities. Moreover, mmWave radar is used to detect biometric information such as the driver’s physical condition and level of concentration, etc., and to monitor the presence and movement of occupants inside the vehicle in occupant monitoring systems. This approach leverages the characteristics of mmWave radar to detect minute movements. Parking assistance systems are an ideal application of mmWave radar due to its advantages such as long detection distance, resistance to weather conditions, and stable detection. Additionally, mmWave radar is getting smaller and more inexpensive, making it easier to integrate into vehicles, which is also contributing to its widespread adoption.

In the smart home and security field, sensors play an active role in various applications. They help improve convenience and safety by detecting the living environment and the condition of residents, and mmWave radar is capable of capturing human movements in detail and providing stable operation at night or in dark areas. In smart home appliances, mmWave radar is mainly installed in lighting, televisions, and air conditioners to enable device control according to human movement. The ability to detect the movements of multiple people and fine movements within a specific detection area is leading to expanded use of mmWave radar. In security systems, mmWave radar enables surveillance that protects privacy compared to direct imaging methods such as cameras by leveraging the unique characteristics of millimeter waves to reliably detect people in adverse environments.

The use of mmWave radar sensors is increasing in healthcare applications. In monitoring systems, mmWave radar enables 24-hour monitoring, including at night, and can be used in locations where camera installation is not feasible due to privacy concerns. These systems assess a person’s entire range of activity to quickly detect falls and other unexpected incidents. In health management systems, the high precision of mmWave radar is used for non-contact measurement by detecting a person’s heart rate, respiratory rate, and other vital information.

mmWave radar is used in various fields, and safety testing has been strengthened in recent years within the European New Car Assessment Programme which evaluates the safety performance of automobiles in Europe. The use of mmWave radar in systems for increasing in-vehicle safety will expand from European vehicles to subsequent adoption in North America and Japan. At the same time, the utilization of mmWave radar in autonomous driving functions will become a factor in significantly expanding the demand for the technology. In applications for use in consumer products, mmWave radar is expected to be used in security and monitoring systems to enhance presence and position detection, which are the basic functions of radar. Additionally, in the market for smart home appliances such as air conditioners and televisions, mmWave radar enhances their multifunctionality to simultaneously use vital sign detection, and the market for such appliances is expected to expand.

The market for mmWave radar sensor modules is expected to significantly grow over the next few years due to the adoption of IoT, the shift toward smart homes, and the advancement of industrial equipment. In particular, high-precision detection using high-frequency bands such as the 60 GHz and 77 GHz bands is attracting attention as an alternative and complementary technology to conventional infrared and ultrasonic sensors. Market forecasts predict a compound annual growth rate (CAGR) of around 10%, with expanded applications across consumer, industrial, and automotive use cases.

Manufacturers that provide the transceiver circuit (RF Front-End) which is the heart of mmWave radar and the IC chips that control the mmWave band are engaged in rapid technological innovation in a field of fierce market competition. In recent years, such technologies have become cheaper and more compact thanks to silicon CMOS and SiGe processes, and inexpensive chips for mass production are now emerging. Such semiconductor manufacturers are expanding their lineups from 77 GHz band products for automotive applications to 60 GHz band products for consumers aiming to adapt mmWave radar to a diverse range of applications.

Module vendors design antennas and substrates, and implement circuits based on the mmWave IC chips supplied by semiconductor manufacturers to offer completed sensor modules. To achieve high precision, they are actively incorporating beamforming technology and synchronous control of multiple channels. Initiatives aimed at thinner modules that consume less power are also becoming an axis of competition. In addition, they are strengthening their own DSP designs and thermal countermeasure technologies to perform the increasingly complex radar signal processing inside the module in a stable manner at high speed.

Algorithms for analyzing received signals are essential for maximizing the precision of radar sensors. Software developers provide distance and speed analysis using FFT (fast Fourier transforms), moving object detection, and noise suppression technologies for complex environments, etc. In recent years, the adoption of machine learning and AI-based moving object classification and environmental recognition technologies has been increasing, and there are an increasing number of cases in which module vendors package specialized algorithms aimed at specific applications (e.g., human detection, gesture recognition, and spatial mapping).