Target Detection and Recognition Based on Active Millimeter-Wave Imaging System

The rapid development of the security inspection system makes the original security inspection equipment gradually unable to meet the needs of the community. The physical characteristics of the millimeter-wave make it more suitable for security imaging systems than X-rays and the active millimeter-wave imaging system has a higher sensitivity and is less affected by the environment than a passive millimeter-wave imaging system. This paper introduces a Ka-band active millimeter-wave imaging system and imaging principle, and uses a new calibration method to correct the images. Finally, the convolutional neural network is used to detect and identify the target.