Entropy-Based Ultra-Wide Band Radar Signals Segmentation for Multi Obstacle Detection

Archive ouverte : Article de revue

Mimouna, Amira | Ben Khalifa, Anouar | Alouani, Ihsen | Amara, Najoua Essoukri Ben | Rivenq, Atika | Taleb-Ahmed, Abdelmalik

Edité par HAL CCSD ; Institute of Electrical and Electronics Engineers

International audience. The development of safe intelligent transportation systems (ITS) has driven extensive research to come up with efficient environment perception techniques with a variety of sensors. In short range settings, Ultra Wide-Band (UWB) radars represent a promising technology for building reliable obstacle detection systems as they are robust to environmental conditions. However, UWB radars suffer from a segmentation challenge: localizing relevant regions of interest (ROIs) within its signals. This article proposes a segmentation approach to detect ROIs in an environment perception-dedicated UWB radar. Specifically, we implement a differential entropy analysis to detect ROIs. We evaluate our technique on a benchmark of more than 47 thousands samples. The obtained results show higher performance in terms of obstacle detection compared to state-of-the-art techniques, and a stable robustness even with low amplitude signals.

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