Self-Supervised Learning for Enhancing Angular Resolution in Automotive MIMO Radars

A novel framework to enhance the angular resolution of automotive radars is proposed. An approach to enlarge the antenna aperture using artificial neural networks is developed using a self-supervised learning scheme. Data from a high angular resolution radar, i.e., a radar with a large antenna aperture, is used to train a deep neural network...

Grouped People Counting Using mm-wave FMCW MIMO Radar

The problem of radar-based counting of multiple individuals moving as a single group is addressed using an mm-wave multiple-input-multiple-output (MIMO) frequency-modulated continuous wave (FMCW) radar. This problem is challenging because the different individuals are closer to each other than the range/azimuth resolution, and their bulk...

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...

Radio wave blind zone in a duct: an analytical approach

Electromagnetic (EM) waves propagate through the atmosphere where they are refracted depending on the composition of the atmosphere. This refraction highly influences the propagation of the EM-waves. Certain atmospheric conditions can cause EM-waves to get trapped within a duct. In these ducts blind zones may occur, where there is no EM-wave...

Radar Calibration by Corner Reflectors with Mass-production Errors

The paper presents the statistical analysis of trihedral corner reflectors RCS in presence of mass production and installation errors. It is shown that the degradation of RCS from its nominal value can be modeled by Beta distribution. The derived probability density functions (PDF) of corner reflector RCS is further exploited to design an...

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...

Auto-calibration of Automotive MIMO Radars Using Simultaneous Localisation and Mapping

This paper presents a new method of automotive MIMO radar self-calibration which uses targets of opportunity embedded in road infrastructure, such as road signs and traffic lights. While conventional offline calibration of a phased array antenna requires accurate knowledge of the positions of calibration targets relative to the radar, such...

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...

Matrix-Pencil Approach-Based Interference Mitigation for FMCW Radar Systems

A novel matrix-pencil (MP)-based interference mitigation approach for frequency-modulated continuous-wave (FMCW) radars is proposed in this article. The interference-contaminated segment of the beat signal is first cut out, and then, the signal samples in the cutout region are reconstructed by modeling the beat signal as a sum of complex...

Auto-calibration of Automotive Radars in Operational Mode Using Simultaneous Localisation and Mapping

This paper presents an analysis of a new method of automotive radar self-calibration which uses targets of opportunity. While conventional offline calibration of a phased array antenna requires accurate knowledge of the positions of calibration targets relative to the radar, such information is not available in a dynamic scenario. To...

Radar Recognition of Multi-Propeller Drones using Micro-Doppler Linear Spectra

This paper proposes to perform radar recognition of multi-propeller drones using micro-Doppler linear spectral pattern in long Doppler coherent processing interval (CPI) circumstances. It focuses on the investigation of the influence of geometry design and motion variables, such as blade number, blade shape, drone’s design geometry and propeller...