When a tracking filter may be designed in the Cartesian coordinate, the covariance of the measurement errors varies according to the range and the bearing of an interested target. In this paper, interacting multiple model based tracking filter is formulated in the Cartesian coordinate utilizing the analytic solution of the steady state Kalman filter, which can be able to consider the variation of the measurement error covariance. 100 Monte Carlo runs performed to verify the proposed method. The performance of the proposed method is compared with the conventional fixed gain and Kalman filter based IMM tracking filter in terms of the root mean square error. The simulation results show that the proposed approach meaningfully reduces the computation time and provides a similar tracking performance in comparison with the conventional Kalman filter based IMM tracking filter.