  Deployment of automated ground vehicles (AGVs) beyond the confines of sunny
and dry climes will require sub-lane-level positioning techniques based on
radio waves rather than near-visible-light radiation. Like human sight, lidar
and cameras perform poorly in low-visibility conditions. This paper develops
and demonstrates a novel technique for robust 50-cm-accurate urban ground
positioning based on commercially-available low-cost automotive radars. The
technique is computationally efficient yet obtains a globally-optimal
translation and heading solution, avoiding local minima caused by repeating
patterns in the urban radar environment. Performance is evaluated on an
extensive and realistic urban data set. Comparison against ground truth shows
that, when coupled with stable short-term odometry, the technique maintains
95-percentile errors below 50 cm in horizontal position and 1 degree in
heading.
