Sense-Through-Foliage target detection using UWB radar sensor networks
In this paper, we propose two signal processing approaches to detect the target obscured by foliage based on real data collected by an Ultra-wide band (UWB) radar sensor. One is a differential-based four-step signal processing approach that estimates and offsets the impulsive clutter; the other approach employs short-time Fourier transform (STFT) to distinguish the target from foliage clutter. Both of these approaches provide better detection performance compared to the common 2-D image algorithm used for UWB radar. From time to time, due to the significant pulse-to-pulse variability of the foliage clutter, neither differential-based nor STFT approach can detect the target. In this case, we propose radar sensor network (RSN) and a RAKE structure in addition to the previous signal processing approaches for data fusion. The result shows that accurate detection can be achieved. Numerical performances have been analyzed for both cases in terms of probability of detection and probability of false alarm.
foliage target detection radar sensor networks short-time fourier transform (stft) differential-based approach