Ground moving target tracking with road constraint

摘要

The Tracking of a Ground Moving Target (GMTI) is a challenging problem given the environment complexity, the target maneuvers and the false alarm rate. Using the road network information in the tracking process is considered an asset mainly when the target movement is limited to the road. In this paper, we consider different approaches to incorporate the road information into the tracking process: Based on the assumption that the target is following the road network and using a classical estimation technique, the idea is to keep the state estimate on the road by using different "projections" approaches. The first approach is a deterministic one based either on the minimization of the distance between the estimate and its projection on the road or on the minimization of the distance between the measurement and its projection on the road. In this case, the state estimate is updated using the projected measurement. The second approach is a probabilistic one. Given the probability distributions of the measurement error and the state estimate, we propose to use this information in order to maximize the a posteriori measurement probability and the a posteriori estimate probability under the road constraints. This maximization is equivalent to a minimization of the Mahalanobis distance under the same constraints. To differentiate this approach from the deterministic one, we called the projection pseudo projection on the road segment. In this paper, we present a comparative study of the performances of these projection approaches for a simple tracking case. Then we extend the study to the case of road intersections in which we present a sequential ratio test in order to select the best road segment.