Frequency Modulated Continuous Wave Radar-Based Navigation Algorithm using Artificial Neural Network for Autonomous Driving

Autonomous driving is a highly complex task, which involves the use of numerous sensors and various algorithms. Testing of algorithms is difficult and therefore mostly done in simulations. Radar technology will play a key part due to various advantages. In this paper we present a solution to one aspect of autonomous driving, which is the development of a detection algorithm on a moving platform, which is capable of tracking and sending the commands to follow a preceding object, by means of sensor data from a low power 60 GHz Frequency Modulated Continuous Wave (FMCW) radar. The moving platform is based on a miniaturized autonomous vehicle that is used for data gathering as well as algorithm evaluation. To the best of the author's knowledge, this is the first time that processing of radar data via Deep Convolutional Neural Networks (DCNN) for navigation purposes is performed in real time on the edge device operating in a real world environment and not simulative.