AI data augmentation through simulation

MSTAR dataset is a publicy available dataset containing SAR imagettes of a set of military targets.

It was collected in 1995 at the Redstone Arsenal, Huntsville, AL by the Sandia National Laboratory using an X-band SAR sensor.

The dataset has become a standard-de-facto validation input for SAR Automatic Target Recognition algorithms

AI data augmentation

In our case study, we leveraged the MSTAR dataset for two different purposes:

Simulator calibration

Training our AI models on MSTAR real data and then test them on SimRAD simulated data

Data augmentation

Training our AI models on SimRAD simulated data and test them on real MSTAR data

Sample results

Interested in the detailed results?

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