Vehicular Motion-based DOA Estimation with a Limited Amount of Snapshots for Automotive MIMO Radar

The problem of high-resolution direction-of-arrival (DOA) estimation based on a limited amount of snapshots in automotive multiple-input multiple-output (MIMO) radar has been studied. The number of snapshots is restricted to minimize target spread/migration in range and/or Doppler domains. A computationally efficient approach for side-looking...

A Novel Approach to Unambiguous Doppler Beam sharpening for Forward-looking MIMO Radar

The ambiguity problem of targets in Doppler beam sharpening (DBS) with forward-looking radar is considered. While DBS is proposed earlier to improve the angular resolution of the radar while keeping the antenna aperture size limited, such a solution suffers from ambiguities in the case of targets positioned symmetrically with respect to the...

Angle-insensitive Human Motion and Posture Recognition Based on 4D imaging Radar and Deep Learning Classifiers

The need for technologies for Human Activity Recognition (HAR) in home environments is becoming more and more urgent because of the aging population worldwide. Radar-based HAR is typically using micro-Doppler signatures as one of the main data representations, in conjunction with classification algorithms often inspired from deep learning...