A Realistic Radar Ray Tracing Simulator for Hand Pose Imaging

TL;DR

This paper introduces a realistic radar ray tracing simulator for hand pose imaging, enabling the generation of synthetic data that closely mimics real radar measurements for improved recognition systems.

Contribution

It presents a novel ray tracing simulation approach for radar hand imaging, including a detailed surface material model, validated against real measurement data.

Findings

High similarity between simulated and real radar images

Effective modeling of complex hand poses

Potential for generating large training datasets

Abstract

With the increasing popularity of human-computer interaction applications, there is also growing interest in generating sufficiently large and diverse data sets for automatic radar-based recognition of hand poses and gestures. Radar simulations are a vital approach to generating training data (e.g., for machine learning). Therefore, this work applies a ray tracing method to radar imaging of the hand. The performance of the proposed simulation approach is verified by a comparison of simulation and measurement data based on an imaging radar with a high lateral resolution. In addition, the surface material model incorporated into the ray tracer is highlighted in more detail and parameterized for radar hand imaging. Measurements and simulations show a very high similarity between synthetic and real radar image captures. The presented results demonstrate that it is possible to generate very realistic simulations of radar measurement data even for complex radar hand pose imaging systems.