In conventional target tracking systems, human operators use the estimated
target tracks to make higher level inference of the target behaviour/intent.
This paper develops syntactic filtering algorithms that assist human operators
by extracting spatial patterns from target tracks to identify
suspicious/anomalous spatial trajectories. The targets' spatial trajectories
are modeled by a stochastic context free grammar (SCFG) and a switched mode
state space model.