Optimal and sub optimal integration of position and doppler sensors for target tracking

Abstract

This paper considers the optimal and sub-optimal integration of radar Doppler and position measurements to track a maneuvering target The optimal integration scheme for position and Doppler measurements within one algorithm is the Kalman Filter. It is shown that the four steady state tracking parameters are dependent only on the Tracking Index, Ʌ (the ratio of the target maneuver to the position measurement noise), and Sensor Noise Ratio, S. The proposed sub-optimal integration process considers the independent operations of an α-β Filter for the position measurements and α-β Filter for the Doppler measurements. The output of the filters are linearly combined to form a target track. An example is presented to show the performance of the α-β tracker; the α-β and β trackers with the linear combiner; and the two-sensor Kalman Filter