Due to the effect of mirror reflection echo,there are inevitably thermal radiation reflection areas (hereinafter referred to as "forged shadow") in the process of pedestrian infrared image acquisition,which affect the pedestrian detection to a certain extent.In this paper,a two stage network detection framework based on lightweight YOLO is proposed to detect the "pedestrian and forged shadow" joint area and accurately locate the shadow location.Firstly,the YOLOv5s lightweight detection algorithm is improved by replacing the original lower sampling part with LSM (Light Sample Module) double branch structure,and the attention mechanism is embedded to improve the feature integration ability of the model to achieve the background filtering and joint region extraction of infrared images.Secondly,the joint area is filled with distortion free rectangle to maintain the original features,and a lightweight shadow of pedestrian location network LS YOLO (Light Structur YOLO) is designed to detect the joint area to obtain the final position coordinates.The experimental results show that the proposed algorithm can meet the real time detection requirements.In the data set,compared with other algorithms,the detection accuracy of forged shadow reaches 95.45%.