Optimal Range and Beamwidth for Radar Tracking of Maneuvering Targets Using Nearly Constant Velocity Filters

For a given radar system on an unmanned air vehicle, this work proposes a method to find the optimal tracking range and the optimal beamwidth for tracking a maneuvering target. An inappropriate optimal range or beamwidth is indicative of the need for a redesign of the radar system. An extended Kalman filter (EKF) is employed to estimate the state of the target using measurements of the range and bearing from the sensor to the target. The proposed method makes use of an alpha-beta filter to predict the expected tracking performance of the EKF. Using an assumption of the maximum acceleration of the target, the optimal tracking range (or beamwidth) is determined as the one that minimizes the maximum mean squared error (MMSE) of the position estimates while satisfying a user-defined constraint on the probability of losing track of the target. The applicability of the design method is verified using Monte Carlo simulations.