Ensure Reliable ADAS / AV Systems

Autonomous driving is one of the most ambitious areas of automotive innovation. Advanced driver assistance systems (ADAS), autonomous driving systems in current mainstream vehicles, and systems that are in the prototype stage will help improve safety.

Keysight provides best-in-class simulation, emulation, and test solutions for mission-critical ADAS and autonomous vehicle (AV) innovations. Our solutions validate and demonstrate the accuracy and dependability of ADAS / AV systems, and ensure the reliability of future system iterations.

Keysight's Automotive Test Solutions Receive Prestigious Industry Awards

As disruptive trends continue to transform the automotive industry, Keysight stands ready to support customers on their ADAS / AV development journeys. Keysight’s Radar Scene Emulator (RSE) and Radar Target Simulator (RTS) received the prominent industry awards below.

Enabling ADAS and AV Capabilities

Achieving the next level in vehicle autonomy demands robust algorithms trained to interpret radar reflections from automotive sensors. But there is a gap. Today, original equipment manufacturers (OEMs) use simulated environments with software-in-the-loop systems to test sensors and control modules. Software simulation is valuable, but it cannot fully replicate the real-world.

The key to developing robust radar sensors and algorithms for ADAS / AV capabilities is full scene emulation in the lab with actual components in a hardware-in-the-loop setup. This setup will put OEMs on the path fo full vehicle autonomy.

White Papers 2022.05.31

Evolving Your ADAS and AV Tests with Emulation Capability

Evolving Your ADAS and AV Tests with Emulation Capability

Creating safe and robust autonomous driving (AD) systems is a complex task. Autonomous vehicles (AVs) have hundreds of sensors, all of which need to work with one another inside the car and with other smart vehicles. The software algorithms enabling autonomous driving features will ultimately need to synthesize all the information collected from these sensors to ensure that the vehicle responds appropriately. These algorithms require testing against millions of complex scenes covering various driving scenarios. Achieving the next level of vehicle autonomy will require many innovations and technological advancements. Continuous investments in sensor technologies such as radar, lidar, and cameras will improve environmental scanning. Each sensor type has its advantages and disadvantages, and they need to complement each other to ensure that the object detection process has built-in redundancy. Software is driving vehicle development trends and topics, such as autonomous driving and electrification. The focus of vehicle development is therefore shifting from hardware to software. Vehicles with ADAS Levels 3 and beyond require testing and validation against the growing number of scenarios and the surrounding environment. Not only will the number of tests increase, but the complexity of the tests will also increase. With the technological advancements and changing development trends, R&D engineers need to reimagine test tactics for ADAS and AV systems. This white paper provides insights and key steps needed to confidently sign off on new ADAS and AV functionality. Download this white paper to find out how you can do the following: Apply DevOps (development and operations) model across software application development cycles, emulate and reproduce test scenarios in the lab, understand the technological concepts of how automotive OEMs emulate the scenes for lab testing, test autonomous driving systems with radar sensors faster and with highly complex, multitarget scenes.


Validate Signal Integrity of Automotive Radar

The automotive industry is adopting wider frequency ranges of the automotive radar from 24 GHz to the 76 – 81 GHz range. These changes mean you will need to consider the design and test challenges with test setups, wideband millimeter-wave (mmWave) measurements, and signal-to-noise ratio (SNR) loss.

Successful automotive radar design verification and performance are achievable by using advanced mmWave technology to simulate, analyze, and characterize various radar signals.

LIDAR Target Simulation

Vehicles of the future will see the world differently through lidar, or light detection and ranging, a key component in autonomous driving. Keysight’s lidar target simulator replicates targets at a distance that are impossible to test in the real world.

You can customize the lidar target simulator to your desired targets and objects with different distances, reflectivity, shapes, and sizes. The lidar target simulator enables you to generate test cases and validate designs, before venturing out to the real-world test environment, which can be costly and time-consuming.

Looking for Other Automotive Testing Solutions?

Keysight Software for Your Automotive Test Needs

Whether you need to analyze and generate standards-compliant automotive radar signals, simulate multiple driving scenarios for ADAS testing, or perform end-to-end security testing, Keysight has what you need to cross the finish line ahead of your competition.


What is ADAS?

ADAS stands for advanced driver assistance system and it is a set of electronic systems capable of assisting drivers as they drive, while removing possible human error. ADAS uses data from a combination of sensor technologies to perceive the world surrounding the vehicle, and either provides information to the driver or takes action when necessary. Some examples of ADAS capabilities are blind-spot detection, cross-traffic alert, and forward-collision warning, which are focused on keeping drivers safe.

What is autonomous driving system?

Autonomous driving system refers to any self-driving vehicle that is capable to sense and navigate through its surrounding environment without any human intervention. Autonomous vehicles are usually equipped with various sensing technologies such as cameras, GPS, radar sensors, and lidar sensors. They are classified from Level 0 to Level 5 based on features and capabilities.

Where does the radar scene emulator (RSE) fit in the world of ADAS?

The RSE's biggest innovation is the ability to generate highly realistic scenes needed to test the algorithms used for autonomous driving systems, in the lab. Automotive OEMs can integrate multiple sensors, emulate scenes, and test part of the system in the lab with actual components that they can place in a hardware-in-the-loop setup. See how you can sharpen your ADAS radar vision with the Keysight Radar Scene Emulator.

What is a rixel?

A rixel is an RF transceiver in the RSE and is small enough to fit into a chip-sized unit. Each rixel is like a pixel on a TV screen. By placing eight rixels on one board, and stacking multiple boards next to each other, the matrix of rixels creates a high-resolution wall. A rixel “displays” distance, velocity, and object size. When joined together, rixels will create complex, multitarget scenes to test autonomous driving systems. Read more about it in the Evolving Your ADAS and AV Tests with Emulation Capabilities white paper.

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