How Aptiv’s Gen 8 Radar Derives More Information for Safe Driving

For many years, automotive radars primarily resolved targets in the horizontal plane, with limited ability to distinguish vertical structure. Research advances led to 4D radar imaging systems, which perceive objects in both the horizontal and vertical dimensions, creating a much fuller picture of the environment around a vehicle and, consequently, a safer and more automated driving experience.

While this was an impressive achievement, the next challenge has been to bring 4D capability to base-level radar sensors. Up to this point, 4D radar systems have been either too simplistic and low-performing or highly complex, requiring multiple transceiver chips and sophisticated processing, which was prohibitively expensive.

Achieving a cost-effective 4D radar with strong performance depends not just on hardware improvements but also on waveform design and antenna array processing. Waveform design enables the measurement of the distance and velocity of an object. Array processing enables measurement of the angle of the object from the radar.

An array can be created from multiple transmit and receive antennas. Each transmit/receive pair contributes a unique measurement, and the resulting antenna geometry is used to measure angle. This technique is known as MIMO (multiple input, multiple output).

MIMO array processing allows multiple transmit and receive antennas to form a much larger virtual antenna array, for improved measurement performance. The waveform design must enable the separation of multiple transmit signals at each receive antenna.

Together, waveform and array processing enable efficient, high-performance measurement of range, velocity and angle.

The Value of Extra Channels for Better Resolution

Aptiv Gen 7 radar, the direct predecessor of Gen 8, uses four transmit antennas and four receive antennas, yielding 16 virtual channels. Gen 8 doubles the number of receive antennas to eight, which in turn doubles the number of virtual channels to 32. Higher channel counts translate directly into better spatial resolution, more precise object classification and improved understanding of the vehicle’s environment.

There are two ways to achieve more channels. The traditional method is to increase channel count by adding more transmit and receive hardware. This approach quickly drives up cost, complexity, power consumption and data‑processing requirements. In contrast, Aptiv’s radar engineers employed a novel method of MIMO to encode a higher number of signals per receive channel, resulting in a more efficient and cost-effective architecture.

The result is a structurally efficient radar system design that delivers significantly more spatial information without forcing the rest of the system to scale linearly in cost. In other words, it gives ADAS more time and confidence to react — not by transmitting more power but by extracting more information from the same physical signals.

Beyond Channel Count: Preparing for the Real World

Gen 8 radar also responds to another growing industry concern: radar interference. As vehicles carry more radar sensors — and roads become more crowded with radar-equipped vehicles — interference from other radars is inevitable.

Earlier systems primarily detected interference and mitigated it by excising affected data, effectively zeroing it out. While functional, this method can introduce artifacts and gaps in perception. Gen 8 radar is designed to support restorative interference detection and mitigation, allowing corrupted data to be reconstructed rather than discarded. While this capability is increasingly expected to be used across the industry, Gen 8 radar incorporates processor-level enhancements to enable it efficiently.

It is difficult and time‑consuming to design and develop novel hardware. But meaningful innovation does not come from hardware alone. For advanced sensing technologies, the real breakthroughs also come from solving complex physics problems that turn raw data into trustworthy information. At Aptiv, we recognize that sensing progress happens at the intersection of physical design and mathematical insight unlocked by AI. By advancing both together, we build systems that deliver safer performance through better detection.