Hybrid Quantum Neural Network Advantage for Radar-Based Drone Detection and Classification in Low Signal-to-Noise Ratio

arXiv:2403.02080v1 Announce Type: cross
Abstract: In this paper, we investigate the performance of a Hybrid Quantum Neural Network (HQNN) and a comparable classical Convolution Neural Network (CNN) for detection and classification problem using a radar. Specifically, we take a fairly complex radar time-series model derived from electromagnetic theory, namely the Martin-Mulgrew model, that is used to simulate radar returns of objects with rotating blades, such as drones. We find that when that signal-to-noise ratio (SNR) is high, CNN outperforms the …

abstract arxiv classification cnn convolution convolution neural network cs.lg detection drone eess.sp hybrid low network neural network noise paper performance physics.app-ph quant-ph quantum quantum neural network radar series signal type