依靠创新的力量影响我们周围的世界
SIGNALS+ 在线快讯订阅
持续关注Signals+，了解有关连接、数字健康、电气化和智能工业的最新见解、信息和想法并加以利用。
MATHWORKS: ADVANCED RF DIGITAL TWINS ACCELERATE SYSTEM DESIGN
KEY TAKEAWAYS
|
The next generation of radar and satellite communications systems is pushing engineering teams into uncharted territory. Modern platforms must support multiple missions, adapt through software updates, and remain relevant for decades, all while operating at increasingly complex RF frequencies and bandwidths.
As phased-array architectures become more sophisticated, traditional prototype-driven design approaches are reaching their limits. Engineers need a way to understand how entire systems will perform long before the first piece of hardware reaches the lab.
MathWorks recognized this challenge early. In collaboration with Analog Devices, the company developed an RF digital twin approach that combines ADI’s validated RF hardware models with system-level simulation. The result is a virtual environment where engineers can explore design trade-offs, evaluate performance under real-world conditions, and connect component-level behavior to mission-level outcomes before committing to physical prototypes.
“We developed an RF digital twin specifically for ADI’s beamformer platform—one that can be used for the design of custom boards at the component level and for end-to-end simulation of complete communications and radar systems. The digital twin enables system integrators to evaluate hardware metrics within the context of their specific application before investing in costly prototypes. ADI’s commitment to providing accurate, high-quality models, along with close collaboration throughout the validation process, made this possible.”Giorgia Zucchelli
Product Marketing Manager, MathWorks
AT A GLANCE
COMPANY
MathWorks is a leading developer of mathematical computing software for designing and developing engineered systems. MATLAB® and Simulink® empower engineering teams to model, simulate, and deploy complex engineered systems across industries including automotive, aerospace, energy, and medical devices. MATLAB provides an integrated environment for algorithm development, data analysis, visualization, and numerical computation, while Simulink enables simulation and model-based design of multidomain and embedded systems. Together, MATLAB and Simulink provide a unified platform that helps engineers address system complexity, accelerate development, and transform concepts into real-world solutions. Founded in 1984, MathWorks employs more than 6,500 people across 34 global offices.
GOAL
Ground RF digital twins in real-world system behavior, enabling engineers to validate and optimize their designs before hardware exists.
CHALLENGE
Component-level analysis falls short for software-defined, multifunction RF platforms.
SOLUTION
Validated ADI hardware models and MathWorks simulation bring RF systems to life virtually.
THE CHALLENGE: PREDICTING REAL-WORLD RF PERFORMANCE EARLY
As radar and satellite communications systems become increasingly software-defined and multifunctional, traditional design approaches are maxing out. Modern platforms must balance competing requirements—from high-linearity communications to high-performance radar—often on the same RF hardware.
Yet developers have historically relied on component-level models and data sheets to predict system behavior. For complex phased-array architectures with thousands of possible operating states, that approach leaves critical questions unanswered.
ADI and MathWorks faced a growing challenge many face in the industry today: how to accurately predict real-world system performance, evaluate design trade-offs, and reduce risk long before a physical prototype exists.
THE SOLUTION: EMPOWERING BREAKTHROUGH DESIGN WITH RF DIGITAL TWINS
To help engineers validate increasingly complex RF systems earlier, ADI and MathWorks developed an RF digital twin framework built on MATLAB and Simulink, MathWorks’ advanced modeling/simulation/system design platforms.
Unlike static component models, RF digital twins are a living framework of executable models that evolve alongside the hardware. Within MATLAB and Simulink, engineers can move between higher-fidelity circuit-envelope models and faster system-level simulations, balancing accuracy and speed as designs mature. This approach enables customers to evaluate ADI products, assess mission-level performance, and explore design tradeoffs long before silicon is available, while continuously refining models as new hardware measurements emerge.
By simulating RF impairments, design trade-offs, and mission-level metrics within realistic operating environments, engineers can evaluate radar, satellite communications, and phased-array systems earlier in development, helping reduce risk and make better-informed design decisions.
The collaboration also created a two-way feedback loop so customers can gain early insight into system behavior, while ADI receives application-level feedback to help shape future product development before silicon is finalized. The result is a faster, more collaborative path from concept to deployment.
RF Digital Twin
|
What It IsAn RF digital twin is a virtual model that combines validated RF hardware models with system-level simulation, enabling engineers to evaluate real-world performance before hardware is built. |
|
Key Capabilities
|
|
Why It Matters
|
THE FUTURE OF ADVANCED RADAR AND SATCOM THROUGH DIGITAL TWINS
The collaboration between ADI and MathWorks demonstrates how digital twins are transforming the way complex RF systems are designed. By connecting validated hardware models with system-level simulation, engineers can explore more design options, evaluate performance earlier, and make decisions with greater certainty before hardware is built.
Looking ahead, advances in AI, digital twins, and digital threads promise to further accelerate development cycles while improving traceability from concept to deployment. Together, ADI and MathWorks are helping create a future where virtual validation becomes an essential part of engineering innovation—enabling smarter, faster, and more predictable system design.
