Adaptive LPD Radar Waveform Design with Generative Deep Learning

arXiv:2403.12254v1 Announce Type: cross
Abstract: We propose a novel, learning-based method for adaptively generating low probability of detection (LPD) radar waveforms that blend into their operating environment. Our waveforms are designed to follow a distribution that is indistinguishable from the ambient radio frequency (RF) background -- while still being effective at ranging and sensing. To do so, we use an unsupervised, adversarial learning framework; our generator network produces waveforms designed to confuse a critic network, which is optimized to differentiate …

abstract ambient arxiv blend cs.lg deep learning design detection distribution eess.sp environment generative low novel probability radar radio type