Abstract: In tracking target with radar application, target dynamics is usually modeled in the Cartesian coordinates, while target measurements are obtained in the original sensor coordinates. A new approach named interacting multiple models-probabilistic data association algorithm based on techniques for measurement convertion is proposed in this paper. Filtering estimation, error covariance and probability of data association related to the algorithm are derived, and new gating techniques for target tracking in clutter is given. Monte-Carlo simulation results indicate that this new approach is effective and feasible.