An IMM Approach for Tracking a Maneuvering Target with Kinematic Constraints Based on the Square Root Information Filter

An efficient interacting multiple model(lMM) approach for tracking a maneuvering target with kinematic constraints is described based on the square Toot information filter(SRIF). The SRIF is employed instead of the conventional Kalman filter since it exhibits more efficient features in handling the kinematic constraints and improved numerical characteristics. The kinematic constraints are considered in the filtering process as pscudomcasurements where the degree of uncertainty is represented by the magnitude of the pscudomeasurement noise variance. The Monte Carlo simulations for the constant speed, maneuvering target are provided to demonstrate the improved tracking performance of the proposed algorithm.