A UWB-MIMO Through-wall Radar Target Detection Algorithm Based on Contrast Detection and Region-growing Feature Discrimination

Ultra-wideband MIMO through-wall radar has been widely used in disaster rescue, anti-terrorism investigation, and intelligent security through multi-antenna cooperative transmission and reception, which not only significantly improves the radial and azimuth resolution, but also has strong medium penetration ability. However, in practical applications, existing systems and mainstream detection algorithms rely too much on the prior modeling of walls and noise parameters, which can easily produce false alarms and missed detections in unknown walls or dynamic scenes. In order to solve above challenges, this paper proposes a joint algorithm based on local contrast detection and adaptive region-growing feature discrimination, which first enhances the local contrast of the PCF-weighted BP radar image, and then introduces the region-growing algorithm to segment target area, and eliminates false alarms according to the geometric features of region. Simulation and field experiments show that the proposed algorithm has better comprehensive performance.