APPLICATION OF EXTENDED KALMAN FILTER TO DYNAMIC TRACKING PROBLEM IN R-LATS

摘要

Many applications requiring dynamic tracking have been needed in large-scale. As a novel distributed measurement system, RLATs is presented and the key techniques are shown in detail. Because of the intrinsical drawback of distributed measurement systems, the Extend Kalman Filter approach is introduced to eliminate the tracking error and improve the tracking accuracy. State space model of RLATs are formulated, and an analytical expression for the linearized measurement function is derived. Comparison with the method of LS simulated data which presented a considerable improvement and stability in accuracy and the proposed EKF method while target's moving speed is less than 100 mm/s.