China and Global Automotive 4D Radar Industry Research Report 2025: From "Optional" to "Essential," 4D Radar's Share Will Exceed 50% by 2030 - ResearchAndMarkets.com

DUBLIN--(BUSINESS WIRE)--The "Automotive 4D Radar Industry Research Report, 2025" report has been added to ResearchAndMarkets.com's offering.

4D radar research: From "optional" to "essential," 4D radar's share will exceed 50% by 2030.

4D imaging radar has transformed from an "optional" to a "must-have" sensor.

4D radar adds the detection and analysis of object height data, perceiving distance, speed, azimuth, and altitude. It is immune to weather and lighting conditions as an indispensable sensor for autonomous driving systems. Its development is mainly driven by the following factors:

Policies. In April 2025, the National Technical Committee of Auto Standardization (NTCAS) of China released the "Technical Requirements and Test Methods for Automatic Emergency Braking Systems of Light-Duty Vehicles (Draft)" to replace the original recommended national standard GB/T39901-2021 for AEB systems.

It suggested that AEB systems should gradually move from "optional installation" to "mandatory standard configuration" and required that from January 1, 2028, M1 and N1 vehicles must be equipped with AEB systems as standard. As relevant AEB regulations impose increasingly stringent requirements on the maximum speed of vehicles before braking, radar faces more stringent performance standards: forward-looking perception systems must have longer detection ranges, stronger weak object recognition and multi-object resolution, and more accurate obstacle height measurement.

With the upgrading of global safety regulations and the increasing penetration rate of L2+/L3 autonomous driving, highway NOA and urban NOA rely on radar, especially 4D imaging radar, to make up for the defects in visual perception and the decline of LiDAR functions (such as in rain, snow, fog, low light, nighttime, severe weather, and obstructions, etc.). For example, when a vehicle is traveling at high speed, the AEB system needs to reliably complete its task. It not only needs to detect large vehicles, but also to recognize smaller, less reflective, or fast-moving objects, such as children crossing the road or motorcycles that have fallen over.

Moreover, such detection often occurs in environments with insufficient light or in rain, snow, or fog. There is also the challenge of detecting stationary objects at a distance, such as cardboard boxes, people next to highway guardrails, and construction equipment. Currently, there are solutions in the industry that enable AEB with a single 4D imaging radar sensor, such as the Aumovio ARS620, which can meet the national AEB standard with a single radar sensor and a detection range of 280 meters (cars and motorcycles) and 174 meters (pedestrians).

Performance leap makes up for the shortcomings in perception. 4D imaging radar solves the problem that traditional radar cannot recognize high-altitude obstacles (such as height restriction poles and road signs) and static objects (such as illegally parked vehicles on ramps). Its angular resolution is improved to 1-2 (equivalent to the level of 8-32 channel LiDAR), and its point cloud density is more than 8 times that of traditional radar (such as 2048 points per frame of the SINPRO SFR-2K). It can clearly restore the object outline and achieve accurate monitoring of objects obscured by vehicles in front (such as the brakes of vehicles in front). Meanwhile, it has all-weather anti-interference capabilities, and its detection range can still reach 300 meters even in harsh environments such as rain, snow, fog and haze, which is significantly better than cameras and LiDAR.

By 2030, 4D radar will account for over 50%.

According to the analyst, 2.737 million and 11.06 million 4D radar sensors were installed in 2024 and 2025 respectively. The figure is projected to exceed 50 million by 2030, with the penetration rate rising from 26.0% in 2025 to 54.5%. Correspondingly, the penetration rates of forward-facing 4D radar and 4D corner radar will also jump, with 4D corner radar showing the fastest growth.

In terms of product selection, OEMs regard 4D radar as an important technological supplement to cameras and LiDAR. Cameras are responsible for high-resolution semantic understanding and color information, LiDAR provides dense 3D shape, and 4D radar offers stable distance, speed, and altitude information in low visibility or complex electromagnetic environments. OEMs consider factors such as performance-cost balance and integrated perception.

4D radar develop toward three directions

Chip processes continue to evolve towards more advanced levels, with continuous improvement in integration and performance.

As the "heart" of radar, the radio frequency MMICs is the most critical in the industry chain. MMICs have undergone iterative upgrades from GaAs to SiGe and then to CMOS. Because CMOS wafers are inexpensive and highly integrated, a radar only requires one RF front-end MMIC and one BBIC, further reducing the system cost by 40%. For example, NXP's 28 nm RFCMOS radar chip - SAF85xx has significantly improved performance compared to the previous 45 nm product, while its cost has been greatly reduced. Calterah's Andes premium 8T8R imaging radar solution connects two 4T4R Andes SoCs (22nm CMOS radar SoC - Andes RoP chip) via C2C, simplifying the hardware design architecture and making it more competitive in terms of system cost. It can achieve a maximum detection range of 350 meters.

As the core components of 4D radar, RF MMICs and processors account for more than 50% of the cost. Currently, there are different solutions for efficiency improvement and cost reduction in the industry, and players choose different routes.

Chip cascading: Combining multiple MMICs (such as two 3T4R chips forming a 6T8R) increases the number of channels to enlarge the aperture. Its advantages lie in a short development cycle and a mature industrial chain, while its disadvantages include high power consumption, large size and low signal-to-noise ratio. For example, WHST's STA77-6 4D radar uses a dual-chip cascade with 6 transmitters and 8 receivers, achieving a detection range of 300 meters. Its 4D ST77-10 has a dual-chip cascade with 16 transmitters and 16 receivers, a field of view of 120 x 30, a resolution of 1 (horizontal) x 1.5 (elevation), and a detection range of 350 meters. This 24T24R imaging radar solution is built on NXP's next-generation high-performance MPU (S32R47) and cascaded 8T8R chips. Paired with NXP's 24T24R array waveguide antenna reference design, the solution can achieve imaging-level accuracy with 576 virtual channels, meaning it can accurately recognize scattered small objects 160 meters away.

Packaging technology is developing towards higher integration, driving the miniaturization and integration of radar modules.

Currently, radar packaging technologies include AiP, RoP, LoP/LiP, and RoC. Among them, AiP, such as Calterah's Alps AiP and TI's AWR2944, sacrifices some detection range in exchange for extreme miniaturization, making it suitable for in-cockpit applications. LoP such as TI's AWR2544 and NXP's SAF85xx improves the signal-to-noise ratio by optimizing the signal path. Its principle is to transmit the radio frequency signal directly from the bottom of the package to the external 3D waveguide antenna, requiring only 2 signal conversions (bare die ? package substrate ? waveguide), reducing 4 conversions required by traditional packaging. It is suitable for satellite-based radar (corner radar, door handle radar) and L3+ autonomous driving (high angular resolution required). The innovative RoP, by replacing traditional feeders with radiators, handles the insufficient channel isolation in AiP, while avoiding the mechanical stability risks incurred by LoP, representing a new direction for 4D imaging radar.

Satellite-based 4D radar achieves 'distributed sensing + centralized computing', helping to reduce cost and improve efficiency.

The core of "satellite-based 4D radar" lies in software-hardware decoupling and centralized computing architectures. It separates computing from the sensor and concentrates it in a powerful central domain controller. The radar only retains necessary radio frequency components (such as MMICs and antennas) for data collection, while processing and decision-making are carried out in the domain controller.

Key Topics Covered:

1 Overview of Automotive 4D Radar

1.1 Overview

1.2 Detection Performance

1.3 4D Radar and 4D Imaging Radar

1.4 Application Scenarios of 4D Radar

1.5 Frame Rate Comparison between High-Definition Radar and Camera/LiDAR

1.6 4D Radar OEM Strategy

1.7 Reasons for the Trend of Installing 4D Imaging Radar in Vehicles

1.8 4D Imaging Radar Industry Chain

2 Automotive 4D Radar Market

2.1 Overview

2.2 Automotive 4D Radar Market

2.3 Radar Market in 2025-2030E

3 Chinese Passenger Car 4D Radar Enterprises

3.1 SINPRO

3.2 WHST

3.3 Cheng-Tech

3.4 Huawei

3.5 Freetech

3.6 Muniu Technology

3.7 Autoroad Technology

3.8 Chuhang Tech

3.9 StarLeading

3.10 Hasco

3.12 Desay SV

3.13 Nova

3.14 Baolong Automotive

3.15 Nanoradar

3.16 Raytron Technology

3.17 Weifu High-Technology

3.18 Huaqin Technology

3.19 Lingtong Technology

4 Foreign Passenger Car 4D Radar Enterprises

4.1 AUMOVIO

4.2 APTIV

4.3 BOSCH

4.4 ZF

4.5 Mobileye

4.6 Altos Radar

5 Automotive 4D Radar Chip/Antenna Enterprises

5.1 TI

5.2 NXP

5.3 Infineon

5.4 Arbe

5.5 Uhnder

5.6 Calterah

5.7 ANDAR

5.8 Guibu Microelectronics

5.9 SenardMicro

5.10 Milliverse (Archiwave)

5.11 Possumic

5.12 SGR Semiconductors

5.13 Southchip Semiconductor Technology

5.14 Boxun Communications

5.15 SPEED Wireless Technology

5.16 Waveland Technology

5.17 SMARTCOMTECH

5.18 HUBER+SUHNER

6 Summary and Trends of Automotive 4D Radar

6.1 Comparison of 4D Radar Chip Companies in Technical Parameters and Customers

6.2 Comparison of 4D Radar Technologies in Parameters

6.3 Vehicle Models Equipped with 4D Radar

For more information about this report visit https://www.researchandmarkets.com/r/idy8hm

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