  This paper investigates the problem of traffic surveillance using an unmanned
aerial vehicle (UAV) and proposes a domain-knowledge-aided airborne ground
moving targets tracking algorithm. To improve the accuracy of multiple targets
tracking, the proposed algorithm incorporates domain knowledge into the joint
probabilistic data association (JPDA) filter as state constraints. The domain
knowledge considered in this paper includes both road information extracted
from a given map and local traffic regulations. Conventional track update
method is modified to enhance the capability of recognition of temporarily
track loss. A variable structure multiple model (VS-MM) method is developed to
assign the road segment to a given target. The effectiveness of proposed
algorithm is demonstrated through extensive numerical simulations.
