Title: Radio Tomography for Roadside Surveillance,
Abstract: Radio tomographic imaging (RTI) has recently been proposed for tracking
object location via radio waves without requiring the objects to transmit or
receive radio signals. The position is extracted by inferring which voxels are
obstructing a subset of radio links in a dense wireless sensor network. This
paper proposes a variety of modeling and algorithmic improvements to RTI for
the scenario of roadside surveillance. These include the use of a more
physically motivated weight matrix, a method for mitigating negative
(aphysical) data due to noisy observations, and a method for combining frames
of a moving vehicle into a single image. The proposed approaches are used to
show improvement in both imaging (useful for human-in-the-loop target
recognition) and automatic target recognition in a measured data set.