What Is Radar Toolbox? - MATLAB & Simulink
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      What Is Radar Toolbox?

      Radar Toolbox includes algorithms and tools for designing, simulating, analyzing, and testing multifunction radar systems. Reference examples provide a starting point for implementing airborne, ground-based, shipborne, and automotive radar systems. Radar Toolbox supports multiple workflows, including requirements analysis, design, deployment, and field data analysis. You can perform link budget analysis and evaluate design trade-offs at the radar equation level interactively with the Radar Designer app. The toolbox includes models for transmitters, receivers, propagation channels, targets, jammers, and clutter. You can simulate radars at different levels of abstraction using probabilistic models and I/Q signal level models. You can process detections generated from these models or from data collected from radar systems using the signal and data processing algorithms provided in the toolbox. You can design cognitive radars that operate in crowded RF shared spectrum environments. For automotive applications, the toolbox lets you model radar sensors at the probabilistic and physics-based levels and simulate data, including micro-Doppler signatures and object lists.  For simulation acceleration or rapid prototyping, the toolbox supports C code generation.

      Published: 24 Aug 2021

      Radar Toolbox provides algorithms and tools for designing, simulating, analyzing, and testing multifunction radar systems. Applications include aerospace and defense surveillance, air traffic control, synthetic aperture radar, and automotive radar. For radar systems engineering, you can utilize the Radar Designer app.

      The Radar Designer app lets you perform analysis based on the radar range equation. This type of analysis is especially useful at early stages of a design, when detailed information about various components is not yet determined. You can also directly evaluate different radar designs against requirements.

      The app includes analytical models for hardware and software components of the radar, such as the beam-shape loss, eclipsing loss, and pulse integration loss. You can quickly add environment losses, including atmospheric effects due to weather such as fog, rain, and snow. You can also model the effects of land and sea clutter. You can also generate a script to recreate the design and results in MATLAB.

      Radar Toolbox scenario generation tools can be used to test the system design, including geospatial data that can be integrated from Mapping Toolbox. You can create realistic scenarios for airborne, ground-based, and shipborne platforms with clutter and target models. You can model platform motion and orientation based on waypoints and trajectories or by simulating inertial navigation systems.

      With Radar Toolbox, you can simulate radar data at different levels of abstraction, probabilistic, or waveform-level. Probabilistic models can be used to quickly test tracking and sensor fusion algorithms. You can use higher fidelity waveform-level simulations to simulate the IQ signal propagation.

      With Radar Toolbox, you can perform closed-loop radar simulation for multifunction radar systems. You can model systems that respond to environmental conditions using waveform selection, PRF agility, frequency agility, and interference mitigation. Radar Toolbox provides signal and data processing algorithms for target detection and tracking.

      For artificial intelligence applications, Radar Toolbox provides tools for synthesizing data to train machine and deep learning models. The toolbox also provides tools for labeling your own radar data for AI models. For more information, please visit the Radar Toolbox product page on mathworks.com.

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