Radar Resource Allocation: Higher Rate or Better Measurements?

Abstract

When tracking maneuvering targets and the need to improve the tracking arises or designing a sensor tracking system, one is often faced with the choice of increasing either the measurement accuracy or rate. The answer to this question is found by assessing the impact on error in the filtered state estimates and the one-step predicted state estimates. In this paper, the tracking of maneuvering targets with a nearly constant velocity (NCV) Kalman filter is considered and the maximum mean squared error (MMSE) in position and velocity are utilized to study the impacts of doubling the measurement accuracy or rate. For each measurement case and the maximum acceleration of a maneuvering target, the process noise variances that minimize the MMSE in the filtered and the one-step predicted track states are used to assess the impacts of doubling either the measurement accuracy or rate. The analysis shows that doubling the measurement accuracy gives a greater reduction in MMSE in filtered position and velocity, while doubling the measurement rate gives a greater reduction in the MMSE in the one-step predicted position and velocity. Process noise variances that minimize the MMSE in the one-step predicted position and velocity estimates are new in this paper.