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
Use MATLAB and Simulink for the design, simulation, and testing of multifunction radar systems. Engineers can:
- perform feasibility analysis,
- predict performance metrics,
- manage resources
- analyze coverage using 3D terrain
- explore sensor array characteristics,
- conduct link budget analysis,
- define system or software architectures
- integrate behavioral models from MATLABand Simulink
- integrate C/C++ into the architectural model.
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Antenna & RF
MATLAB and Simulink can help engineers to design and simulate RF, antenna, and digital systems in a unified environment.
Both can facilitate prototyping, system integration, and performance analysis using high-level models, S-parameters, and RF measurements.
signal processing
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.
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DATA PROCESSING
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, so engineers can assess system architectures that combine grid-level, detection-level & object-or track-level fusion.
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TARGETS AND ENVIRONMENT
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.
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HARDWARE & DEPLOYMENT
Radar engineers leverage MATLAB & 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.
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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.
