Multipath Ghost Recognition and Suppression Method Based on Template Matching for Indoor Human Detection and Location

Abstract

Indoor human detection and location is a prominent research area within the Internet of Things, which can be effectively realized using radar technology. However, the electromagnetic waves will be reflected by the wall, leading to multipath ghosts in radar image, resulting in increased false alarm rates and degraded target location accuracy. In order to address this challenge, a multipath ghost recognition and suppression method based on template matching is proposed in this article. It is proved that the shape can be modeled as ellipse and the major axis and rotation angle of ghost is different from that of target. Two distinct features are calculated and used to achieve ghost recognition, and ghost mask is generated further. The effectiveness and robustness of the proposed method are validated through simulations and experimental results. Particularly, the proposed method does not depend on the information of building layout and is geometry-layout-free.