The invention discloses a radar generated color semantic image system and method based on a conditional generative adversarial network, which belong to the technical fields of sensors and artificial intelligence. The system includes a data acquisition module based on radar point cloud and a camera, an original radar point cloud up-sampling module, a model training module based on a conditional generative adversarial network, and a model using module based on a conditional generative adversarial network. The method provided by the invention includes the following steps: constructing a radar point cloud-RGB image training set; constructing a conditional generative adversarial network based on a convolutional neural network to train a model; and finally, enabling the model to generate a colorroad scene image with meanings in real time in a vehicle environment by using sparse radar point cloud data and the trained conditional generative adversarial network only, and using the color road scene image in automatic driving and auxiliary driving analysis. The network efficiency is higher. The adjustment of network parameters can be speeded up, and an optimal result can be obtained. High accuracy and high stability are ensured.
Radar generated color semantic image system and method based on conditional generative adversarial network