ISAR motion parameter estimation using state-space modeling

In this paper, an approach based on state-space modelization and use of an extended Kalman filter (EKF) is applied and evaluated for the problem of focusing distorted inverse synthetic aperture radar (ISAR) images when the target motion is confined to a two-dimensional plane. The use of a multi-sensor array allows the exploitation of spatial information and leads to the consideration of multiple filters with different observation equations. The problem is transformed into parameter estimation of multi-component (MC) polynomial-phase signals (PPS) when impinging on a multi-sensor array. We show through a simulation that the algorithm provides an effective method of achieving accurate motion parameter estimation.