Target Tracking With Revisit Interval Uncertainty for Rotating Radars

In rotating radars, the revisit interval is time variant and uncertain due to its dependence on target states and the disturbance of process noise, violating the assumption of prior known revisit interval in conventional tracking algorithms. In this article, the formulation of state transition and target state estimation with revisit interval uncertainty are investigated. The dependence of the revisit interval on the antenna rotation and target states is formulated to describe target dynamics, together with the traditional state transition equation. A space-time joint processing method based on Newton-Raphson iteration is presented to calculate the revisit interval and the predicted state simultaneously. Such a numerical solution is considered as a general function reflecting the target state transition. The unscented Kalman filter (UKF) is then utilized to deal with the nonlinear filtering problem and produce state estimates. In addition, a filter initialization method based on the target dynamics and the unscented transformation is presented to produce consistent initial state estimates. Experimental results illustrate the superiority of the proposed space-time joint processing unscented Kalman filter (STJP-UKF). The performance of the STJP-UKF is superior to that of the standard UKF, and comparable with that of the UKF with known revisit intervals.