A translational motion estimation and compensation method is proposed based on the parametric method by multiple stations in the distributed inverse synthetic aperture radar (ISAR) imaging. For ship targets with complex motion, the distributed ISAR increases the cross-range resolution of the image by expanding the observation angle. However, the translation compensation methods by a single station will destroy the correlation between the echoes, which reduces the image quality, and a more accurate joint translation compensation method is required. Multi-static observation is obtained in the Distributed system, which we can utilise in the parameter estimation: 1) joint Doppler estimation, 2) station angle estimation, and 3) rotation velocity estimation. Based on the above estimations, the velocity vector and the acceleration vector of the target can be obtained, and then the translational motion compensation can be realised parametrically. The algorithm processing chain is presented in this paper. Finally, the numerical simulations with four stations are presented to verify the effectiveness and the robustness of the proposed algorithm.
For ship targets with complex motion, it is difficult for the traditional monostatic inverse synthetic aperture radar (ISAR) imaging to improve the cross-range resolution by increasing of accumulation time. In this paper, a distributed ISAR imaging algorithm is proposed to improve the cross-range resolution for the ship target. Multiple stations are used to observe the target in a short time, thereby the effect of incoherence caused by the complex motion of the ship can be reduced. The signal model of ship target with three-dimensional (3-D) rotation is constructed firstly. Then detailed analysis about the improvement of crossrange resolution is presented. Afterward, we propose the methods of parameters estimation to solve the problem of the overlap or gap, which will cause a loss of resolution and is necessary for subsequent processing. Besides, the compressed sensing (CS) method is applied to reconstruct the echoes with gaps. Finally, numerical simulations are presented to verify the effectiveness and the robustness of the proposed algorithm.
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