International Symposium on Telecommunication (IST)

Home / 11th International Symposium on Telecommunication (IST'2024)

Automotive Radar Simulator Based on Ray-Tracing and Machine Learning

Authors :

Jamal Kazazi¹ Alireza Mahdavi² Mahmoud Kamarei³ Mohammad Fakharzadeh⁴

1- university of tehran 2- university of tehran 3- university of tehran 4- sharif university of technology

Keywords :

FMCW radar،Ray tracing،Radar Simulator،Automotive Radar،LSTM،Radar،radar dataset generator

Abstract :

In this paper, we have designed software that can simulate a scenario of a road with several vehicles or pedestrians. Each target has 4 parameters: its type, speed, distance, and RCS. The software generates simulated signals using two methods: Ray-tracing and using Neural Networks which are trained with a real radar dataset. The Neural Network part uses a Long Short-Term Memory (LSTM) Network for Scenarios which have more than two targets and a simple multilayer perceptron (MLP) network for simulating scenarios with just one target. After starting the simulation, it shows an animation of the movement of different targets on a road. In addition, it can save the radar signals that are received by the radar receiver and draw 4 plots from signals as the real location of targets in the Range-Doppler map (RD map), 1D FFT of the signal, 2D FFT image, and estimated location of targets. It can generate a specific number of random scenarios for dataset generation in machine learning research. It also can consider the impact of antenna patterns on the received radar signals.