The progress brought by the deep learning technology over the last decade has inspired
many research domains, such as radar signal processing, speech and audio recognition …

With the rapid development of automated vehicles (AVs), more and more demands are
proposed towards environmental perception. Among the commonly used sensors, MMW …

A wide range of advanced deep learning algorithms have recently been proposed for image
classification and object detection. However, the effectiveness of these methods can be …

Radar is a key component of the suite of perception sensors used for safe and reliable
navigation of autonomous vehicles. Its unique capabilities include high-resolution velocity …

With recent developments, the performance of automotive radar has improved significantly.
The next generation of 4D radar can achieve imaging capability in the form of high …

A comprehensive and well-structured review on the application of deep learning (DL) based
algorithms, such as convolutional neural networks (CNN) and long-short term memory …

Radar target detection (RTD) is a fundamental but important process of the radar system,
which is designed to differentiate and measure targets from a complex background. Deep …

Modern radar systems have high requirements in terms of accuracy, robustness and real-
time capability when operating on increasingly complex electromagnetic environments …

Scene understanding for automated driving requires accurate detection and classification of
objects and other traffic participants. Automotive radar has shown great potential as a sensor …

The development of autonomous vehicles and unmanned aerial vehicles has led to a
current research focus on improving the environmental perception of automation equipment …