AI for Radar
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
Improving Weather Radar Moment Estimation with Convolutional Neural Networks
Train and evaluate convolutional neural networks (CNN) to improve weather radar moment estimation.
- Since R2024b
- Open Live Script
LPI Radar Waveform Classification Using Time-Frequency CNN
Train a time-frequency convolutional neural network (CNN) to classify received radar waveforms based on modulation scheme.
- Since R2024a
- Open Live Script
Generate Novel Radar Waveforms Using GAN
Generate new radar waveforms using a Wasserstein generative adversarial network with a gradient penalty (WGAN-GP).
- Since R2024a
- Open Live Script
Maritime Clutter Suppression with Neural Networks
Train and evaluate a convolutional neural network to remove clutter returns from maritime radar PPI images using the Deep Learning Toolbox™.
- Since R2022b
- Open Live Script
SAR Target Classification Using Deep Learning
Create and train a simple convolution neural network to classify SAR targets using deep learning.
- Since R2021b
- Open Live Script
Label Radar Signals with Signal Labeler
Label the time and frequency features of pulse radar signals with added noise.
- Since R2021a
- Open Live Script
Pedestrian and Bicyclist Classification Using Deep Learning
Classify pedestrians and bicyclists based on their micro-Doppler characteristics using deep learning and time-frequency analysis.
- Since R2021a
- Open Live Script
Radar Target Classification Using Machine Learning and Deep Learning
Classify radar returns using machine and deep learning approaches.
- Since R2021a
- Open Live Script
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).
- Since R2021a
- Open Live Script
Hand Gesture Classification Using Radar Signals and Deep Learning
Classify ultra-wideband impulse radar signal data using a MISO convolutional neural network.
(Deep Learning Toolbox)
Human Health Monitoring Using Continuous Wave Radar and Deep Learning
Reconstruct electrocardiogram signals using a bidirectional long short-term memory network and wavelet multiresolution analysis.
(Deep Learning Toolbox)
Ship Detection from Sentinel-1 C Band SAR Data Using YOLOX Object Detection
Detect ships from Sentinel-1 C Band SAR Data using YOLOX object detection.
(Image Processing Toolbox)
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