Human-vehicle classification plays an important role in advanced driver assistance systems
(ADAS). The use of millimeter wave (mmWave) radar sensor in human-vehicle classification …

This paper proposes a method to simultaneously detect and classify objects by using a deep
learning model, specifically you only look once (YOLO), with pre-processed automotive …

In this study, a human–vehicle classification using a feature‐based support vector machine
(SVM) in a 77‐GHz automotive frequency modulated continuous wave (FMCW) radar …

This paper presents a detection method of remotely identifying a potential active shooter
with a concealed rifle/shotgun based on radar micro-Doppler and range-Doppler signature …

In autonomous driving vehicles, the emergency braking system uses lidar or radar sensors
to recognize the surrounding environment and prevent accidents. The conventional …

In this paper, we propose a Doppler-spectrum feature-based human–vehicle classification
scheme for an FMCW (frequency-modulated continuous wave) radar sensor. We introduce …

Unique micro-Doppler signature (μ-D) of a human body motion can be analyzed as the
superposition of different body parts μ-D signatures. Extraction of human limbs μ-D …

In this paper, we proposed a human-vehicle classification scheme using a Doppler spectrum
distribution based on 2D Range-Doppler FMCW (Frequency Modulated Continuous Wave) …

A new approach to micro-Doppler signal analysis is presented in this article. Novel chirp rate
estimators in the time-frequency domain were used for this purpose, which provided the …

Micro-Doppler and range-Doppler provide useful information related to the movement of a
human subject. This work demonstrates the feasibility of remotely identifying a potential …