Discrimination of human targets for radar surveillance via micro-Doppler characteristics

Abstract

An approach is examined for reducing false alarms during detection of human targets via radar surveillance from moving platforms. The ability to distinguish between human target and clutter discrete micro-Doppler signatures is quantified using simulated and real data collected using the DORC X-band wideband experimental airborne radar. Signal processing methodologies to extract key target signature characteristics are discussed along with separability of target classes and classifier performance.