Joint Translational Motion Compensation for Multitarget ISAR Imaging Based on Integrated Kalman Filter

Traditionally, when multiple targets appear within the radar beam at the same time, the range profiles of different targets are coupled together, the existing algorithms usually image each target separately due to the different motion states of the targets, making it impossible to image multiple targets simultaneously. To overcome this problem, this paper proposes a joint translational motion compensation and imaging method for multiple targets based on an integrated Kalman filter (IKF), which can realize the integration of tracking and imaging for multiple targets. Firstly, an integrated Kalman filter for wideband radar tracking is employed to predict as well as accurately estimate the next-moment motion state of multiple targets simultaneously. Then, with the precisely estimated motion state of the next moment, a joint translational compensation method with a blocked Fourier compensation matrix (BFCM) is proposed in order to compensate for the translational motion of multiple targets simultaneously, which uses the characteristics of the multi-target’s echo signal separated in the range time domain. Finally, by using the IKF and BFCM, the sequential translational motion compensation for multiple targets can be achieved, and the well-focused ISAR images for multi-target are obtained. Finally, the effectiveness of the method is verified by simulated and real data.