  LADARs mounted on mobile platforms produce a wealth of precise range data on
the surrounding objects and vehicles. The challenge we address is to infer from
these raw LADAR data the location and orientation of nearby vehicles. We
propose a novel view-dependent adaptive matched filter for obtaining fast and
precise measurements of target vehicle pose. We derive an analytic expression
for the matching function which we optimize to obtain target pose and size. Our
algorithm is fast, robust and simple to implement compared to other methods.
When used as the measurement component of a tracker on an autonomous ground
vehicle, we are able to track in excess of 50 targets at 10 Hz. Once targets
are aligned using our matched filter, we use a support vector-based
discriminator to distinguish vehicles from other objects. This tracker provides
a key sensing component for our autonomous ground vehicles which have
accumulated hundreds of miles of on-road and off-road autonomous driving.
