Photonics-based radar expands the bandwidth of traditional radars and enhances the radar range resolution. This makes it possible to recognize small-size targets using the high resolution range profiles (HRRPs) acquired by a photonics-based broadband radar. In this paper, we investigate the performance of small target recognition using HRRPs of a photonics-based radar with a bandwidth of 8 GHz (28-36 GHz), which is built based on photonic frequency multiplication and frequency mixing. A convolutional neural network (CNN) is used to extract features of the HRRPs and classify the targets. In the experiment, recognition of four types of small-size targets is demonstrated with an accuracy of 97.16%, which is higher than target recognition using a 77-GHz electronic radar by 31.57% (2-GHz bandwidth) and 8.37% (4 GHz-bandwidth), respectively. Besides the accuracy, target recognition with photonics-based radar HRRPs is proved to have good generalization capability and stable performance. Therefore, photonics-based radar provides an efficient solution to small target recognition with one-dimension HRRPs, which is expected to find import applications in air defense, security check, and intelligent transportation.