A theoretical development of a novel approach for target tracking based on multiple patterns extracted from measurement sequences is presented in this paper. The introduction of patterns leads to a new paradigm for developing high performance algorithms. An interacting multipattern probabilistic data association (IMP-PDA) algorithm is developed, taking advantage of clever formulation of the interacting multiple model (IMM) approach. The IMP-PDA algorithm employs distance, directional and maneuver information for data association, which enhances significantly the capability of discriminating correct measurements from false measurements.