In this paper, we present a multi target particle filter DOA tracker that can incorporate road prior information at a single array node. The filter uses a batch of DON's to determine the state vector, based on an image template matching idea. The filter likelihood is derived with the joint probability density association principles so that no DOA measurement is associated to more than one target. The filter state update has the target DOA, the target velocity over range ratio, and the target heading parameters. We present two approaches for incorporating the road information. In the first approach, the road prior is injected at the weighting stage of the tracker, where a raised mixture Gaussian distribution, derived from the road headings at the target DOA, constraints the particles. The second approach is based on modifying the state update function with a compound model, where a mixture of the constant velocity model and the road information is used. In this case, the filter uses an online EM algorithm to update the state vector along with the mixture components. Computer simulations demonstrate the performance of the approaches.