In a study published in the IET journal Radar, Sonar & Navigation, the team shows that convolutional neural networks (CNNs), a fundamental computer vision technology, can significantly improve radars’ ability to detect, localise and track objects.
Traditional radar systems, which have been used since World War II, have reached their peak, but the scientists’ approach combines modern artificial intelligence techniques to overcome these limitations. The researchers have released “RASPNet,” a massive open-source dataset containing more than 16 terabytes of data from diverse U.S. landscapes.
This dataset is intended to help other researchers develop and test new AI algorithms for radar systems.
Source: Ferra
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