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

Abstract

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.