Radar Systems
RADAR systems with Matlab & simulink
Radar engineers leverage MATLAB and Simulink to accelerate the design process of radar systems, from antenna arrays to radar signal processing algorithms, as well as data processing and control.
With MATLAB and Simulink, radar engineers can:
- Conduct feasibility studies, predict system performance, and perform 3D terrain coverage analysis
- Design and analyze radar system architectures interactively
- Design, analyze, integrate, and visualize antenna elements, arrays, and RF components
- Model the propagation channel, targets, jammers, and clutter
- Design and test multifunction, multisensor phased array tracking and positioning systems
- Generate code for prototyping or production in floating or fixed-point formats, for MCUs, GPUs, SoCs, and FPGAs
- Synthesize data and train deep learning models for applications such as target classification and modulation identification
RADAR SYSTEMS
Engineers use MATLAB and Simulink to streamline the end-to-end design, simulation, and testing of multifunction radar systems.
With these tools, radar system engineers can perform in-depth feasibility analyses, predict system performance through parameterized metrics, optimize resource management, and conduct comprehensive coverage analysis using 3D terrain data. They can also investigate sensor array and waveform characteristics to perform detailed link budget analysis. Additionally, engineers can define and evaluate both system and software architectures, while subsystem engineers can seamlessly integrate behavioral models—developed in MATLAB, Simulink, or C/C++—into the broader architectural framework.
(See also “How do radars work“)
Antenna & RF
Antenna and RF engineers employ MATLAB and Simulink as an integrated design platform to prototype and refine signal chain components, including RF, antenna, and digital elements. This collaborative environment allows for the consolidation of various team contributions into a unified system-level executable model.
By combining both high-level and high-fidelity models, engineers can simulate the interactions between components, critically assess design trade-offs, and evaluate how different design choices impact overall system performance. Furthermore, the inclusion of S-parameters and other RF measurements within system simulations enhances the precision and depth of performance analysis.
Signal Processing
Using MATLAB, Simulink, and advanced applications, radar signal processing engineers can craft and analyze multifunction phased array systems that demand exceptional flexibility—whether in frequency, PRF, waveform, or beam pattern agility. These engineers are equipped to simulate the full scope of radar and electronic warfare (EW) system behaviors, along with their interactions with targets, across platforms ranging from terrestrial to airborne and maritime.
By leveraging a rich library of integrated signal processing algorithms, engineers can execute sophisticated tasks such as beamforming, matched filtering, direction of arrival (DOA) estimation, and target detection—enhancing both performance and adaptability across diverse operational environments.
DATA Processing
Radar data processing engineers use MATLAB and Simulink to design, simulate, and test systems that integrate data from multiple sensors to support situational awareness and precise localization.
By modeling radar, EO/IR, IMU, and GPS sensors in MATLAB, engineers can evaluate their algorithms against both real-world and synthetic data. The platform offers an extensive library of multi-object tracking and estimation filters, enabling engineers to assess system architectures that combine grid-level, detection-level, and object- or track-level fusion. This allows for rigorous performance validation through metrics that compare results to ground truth.
Targets and Environment
Radar and electronic warfare (EW) engineers rely on MATLAB and Simulink to model complex phenomena such as wave propagation, clutter, jamming, interference, and target motion—encompassing both constant velocity and acceleration.
Engineers can also simulate target cross-section and atmospheric attenuation using line-of-sight (LOS) propagation models. These models calculate signal propagation through various atmospheric conditions, including gases, rain, fog, and clouds, providing a comprehensive understanding of environmental impacts on radar performance.
HArdware & Deployment
Radar engineers leverage MATLAB and Simulink models across a variety of deployment targets within production environments. These models can be converted to C, C++, HDL, or CUDA® for seamless deployment on embedded or edge devices.
Additionally, engineers can integrate these models with proprietary enterprise desktop or server applications. To enhance simulation and application performance, engineers can accelerate processing using generated C/C++ and MEX code, or by utilizing GPUs and node pools.
AI for Radar
Radar engineers leverage MATLAB to develop artificial intelligence-driven applications in areas such as cognitive radar, software-defined radio, and intelligent receivers.
By synthesizing data within MATLAB models, engineers can train deep learning and machine learning networks, enabling advanced applications such as modulation identification and target classification.
