Abstract (MobiCom'15)
The future of mobile computing involves autonomous drones, robots
and vehicles. To accurately sense their surroundings in a variety of
scenarios, these mobile computers require a robust environmental
mapping system. One attractive approach is to reuse millimeterwave
communication hardware in these devices, e.g. 60GHz networking
chipset, and capture signals reflected by the target surface.
The devices can also move while collecting reflection signals, creating
a large synthetic aperture radar (SAR) for high-precision RF
imaging. Our experimental measurements, however, show that this
approach provides poor precision in practice, as imaging results are
highly sensitive to device positioning errors that translate into phase
errors. We address this challenge by proposing a new 60GHz imaging
algorithm, RSS Series Analysis, which images an object using
only RSS measurements recorded along the device’s trajectory. In
addition to object location, our algorithm can discover a rich set
of object surface properties at high precision, including object surface
orientation, curvature, boundaries, and surface material. We
tested our system on a variety of common household objects (between
5cm–30cm in width). Results show that it achieves high
accuracy (cm level) in a variety of dimensions, and is highly robust
against noises in device position and trajectory tracking. We believe
that this is the first practical mobile imaging system (re)using
60GHz networking devices, and provides a basic primitive towards
the construction of detailed environmental mapping systems.
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