Short-Range FMCW Monopulse Radar for Hand-Gesture Sensing
Pavlo Molchanov, Shalini Gupta, Kihwan Kim, and Kari Pulli
NVIDIA Research, Santa Clara, California, USA
Abstract—Intelligent driver assistance systems have become
important in the automotive industry. One key element of such
systems is a smart user interface that tracks and recognizes
drivers’ hand gestures. Hand gesture sensing using traditional
computer vision techniques is challenging because of wide vari-
ations in lighting conditions, e.g. inside a car. A short-range
radar device can provide additional information, including the
location and instantaneous radial velocity of moving objects. We
describe a novel end-to-end (hardware, interface, and software)
short-range FMCW radar-based system designed to effectively
sense dynamic hand gestures. We provide an effective method
for selecting the parameters of the FMCW waveform and for
jointly calibrating the radar system with a depth sensor. Finally,
we demonstrate that our system guarantees reliable and robust
performance.
I. INTRODUCTION
Hand gestures are a natural form of human communication.
In automobiles, a gesture-based user interface can improve
drivers’ safety. It allows drivers to focus on driving while
interacting with the infotainment or controls (e.g., air con-
ditioning) in the car. A short-range radar sensor can add
extra modalities to gesture tracking/recognition systems. One
of these modalities is the instantaneous radial velocity of the
driver’s moving hand. Advantages of the radar system are (1)
robustness to lighting conditions compared to other sensors,
(2) low computational complexity due to direct detection of
moving objects, and (3) occlusion handling because of the
penetration capability of EM waves.
Prior work in hand gesture recognition primarily used depth
and optical sensors [1]. Optical sensors do not provide accurate
depth estimation, and depth sensors can be unreliable outdoors
where sunlight corrupts their measurements. Technically time-
of-flight (TOF) depth and radar sensors are similar, as they
both measure the delay of the signal traveling to and from
the object. However, radar sensors use lower frequencies,
which allows for the estimation of the phase of the wave and
consequently the Doppler shift. Using radar-like sensors for
gesture sensing has been studied recently [2], [3], [4]. In most
of these works, the hand is modeled as a single rigid object.
However, in reality, it is not and in this work we model the
hand as a non-rigid object. This allows us to perceive the
hand as a multi-scatterer object and to capture its local micro-
motions.
In this work, we describe a novel end-to-end (hardware, in-
terface, and software) short-range radar-based system designed
and prototyped to effectively measure dynamic hand gestures
(see Fig. 1). The idea behind the proposed radar system for
gesture recognition is the fact that the hand behaves as a
non-rigid object. Therefore, in the context of dynamic gesture
recognition, a hand gesture produces a multiple reflections
4 antennas
Analog circuits
Microcontroller
Radar chips
Tx
Rx1
Rx2
Rx3
Fig. 1: A short-range monopulse FMCW radar prototype built for
gesture sensing (left). The black plastic component encases four
rectangular waveguide antennas (SMA to WR42 adapters).
from different parts of the hand with different range and
velocity values that vary over time. Because of this, different
dynamic hand gestures produce unique range-Doppler-time
representations, which can be employed to recognize them.
We found that Frequency Modulated Continuous Wave
(FMCW) radar with multiple receivers (monopulse) is best
suited for hand gesture sensing. It can estimate the range
and velocity of scatterers, and the angle of arrival of objects
that are separated in the range-Doppler map. The information
from monopulse FMCW radar is also easier to fuse with
depth sensors, because they provide spatial information of
the object in 3-dimensions (3D). We used three receivers
and the monopulse technique for estimating the azimuth and
elevation angles of moving objects, which enabled our system
to estimate the spatial location of objects and their radial
velocity.
To the best of our knowledge, our radar-based solution for
hand gesture sensing is the first of its kind. Our system is
similar to long-range radars currently employed in automobiles
to sense external environments, but for our solution, which
was designed to operate inside a car, we adapted these radar
principles to the short-range (< 1m) scenario.
The proposed radar system is part of a multi-sensor system
for drivers’ hand-gesture recognition [5]. In this paper we
describe in detail the design and signal processing procedures
of the radar system.
The paper is organized as follows. In the Section II, we
describe the design and implementation of our proposed radar
system. Experiments to validate the radar system’s operation
with measurements of a disk, a pendulum and a hand are
presented in Section III. We conclude the paper in Section IV.
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