Neurosymbolic-AI Based Identification and Geolocation of Micro-UASs using Fused 5.85 GHz Micro-Doppler and 77 GHz FMCW Radars
Conference
Edirisinghe, D, Haputhanthri, L, Herath, D et al. (2026). Neurosymbolic-AI Based Identification and Geolocation of Micro-UASs using Fused 5.85 GHz Micro-Doppler and 77 GHz FMCW Radars
.
Edirisinghe, D, Haputhanthri, L, Herath, D et al. (2026). Neurosymbolic-AI Based Identification and Geolocation of Micro-UASs using Fused 5.85 GHz Micro-Doppler and 77 GHz FMCW Radars
.
This paper presents the design and implementation of a multi-band multi-mode radar for reliable detection and identification of micro unmanned aerial systems (UASs). A rotational micro-Doppler continuous-wave radar operating at 5.85 GHz and a frequency-modulated continuous-wave (FMCW) radar operating with 77-80 GHz bandwidth are used for multi-modal radio frequency (RF) sensing, localization and detection. Fusion of the two radars is achieved with a neurosymbolic artificial intelligent model. Cyclostationary feature extraction is used for the micro-Doppler signature extraction. Wavelet domain feature extraction is used on the FMCW radar outputs. A custom neural engine is used for multi-modal sensor fusion across the two RF bands and radar types.
