IEEE ICPRS 2023

Radar target detection based on deep learning techniques

Radar target detection is a process that requires the reception, processing and analysis of radio-frequency signals reflected over long distances. This process must meet several high performance parameters to ensure responsiveness to threats in the environment. Current systems base their operation on algorithms that have poor performance when operating with a low SNR (signal to noise ratio), a situation that is common when analyzing distant targets in uncontrolled environments. However, the improvement in deep learning algorithms has led to supervised training systems that reflect better results when acting as classifiers. Therefore, this talk presents the problem of radar target detection and classical detection algorithms. After that, comparisons between a classical Bayesian algorithm (AR LMS MEAN) and machine/deep learning algorithms are presented. The results discussed in this talk show that deep learning greatly improves radar target detection for low SNR levels. Finally, some future works are reviewed.

Enrique Vinicio Carrera received his bachelor's degree in electronic engineering from the Armed Forces University - ESPE, Ecuador, in 1992, and his master's degree in electrical engineering from the Pontifical Catholic University of Rio de Janeiro, Brazil, in 1996. In 1999, he received his doctoral degree in computer engineering from the Federal University of Rio de Janeiro, Brazil. He was a visiting scholar at the University of Rochester, USA, in 1999. From 2000 to 2004, he was a postdoctoral associate in the Department of Computer Science at Rutgers University, USA. Dr. Carrera was also an associate professor at University San Francisco of Quito, Ecuador, from 2004 to 2011. Since 2011, he has been professor at the Armed Forces University - ESPE, Ecuador. He has also collaborated as an external professor at King Juan Carlos University, Spain, since 2015. Currently, he is an IEEE Senior Member and has an appointment as a Distinguished Visitor at the IEEE Computer Society. Dr. Carrera has participated in approximately 20 research projects, holds more than 100 scientific publications in recognized journals and conferences with more than 3000 citations. His main research areas include signal processing and computational intelligence.