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AI for Radar

Labeling of radar signals, simulated radar signals to train machine and deep learning models, target classification, signal classification

You can label radar signals using the Signal Labeler app. Augment datasets by simulating radar waveforms and echos for objects with simple geometries such as cylinders and cones. Simulate micro-Doppler signatures of animated objects such as helicopters, pedestrians and bicyclists. Train machine learning and deep learning networks to classify targets and signals.

Featured Examples

Labeling Radar Signals with Signal Labeler

Labeling Radar Signals with Signal Labeler

Label the time and frequency features of pulse radar signals with added noise.

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Pedestrian and Bicyclist Classification Using Deep Learning

Pedestrian and Bicyclist Classification Using Deep Learning

Classify pedestrians and bicyclists based on their micro-Doppler characteristics using a deep learning network and time-frequency analysis.

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Radar Target Classification Using Machine Learning and Deep Learning

Radar Target Classification Using Machine Learning and Deep Learning

Classify radar returns using machine and deep learning approaches.

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Radar and Communications Waveform Classification Using Deep Learning

Radar and Communications Waveform Classification Using Deep Learning

Classify radar and communications waveforms using the Wigner-Ville distribution (WVD) and a deep convolutional neural network (CNN).

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Radar Toolbox Documentation

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