IMAGE FUSION FOR TRACKING MANEUVERING TARGETS

It is known that improvements in target tracking can be achieved by us ing multiple sensors. Most commonly, the individual measurement sequen ces are merged using a variant of linear algorithms. The approach prop osed here differs from the conventional one in that nonlinear methods of data fusion are proposed to account for the peculiarities of the di fferent measurement categories. This technique, called complementary f usion, is illustrated with the problem of tracking an agile target. It is shown that complementary fusion not only leads to higher fidelity tracking, but it also permits the more efficient utilization of the pr imary sensor.