ISAR Image 3D Reconstruction Based on Radar Network

Traditional 2-D inverse synthetic aperture radar (ISAR) imaging can be regard as an inverse problem to reconstruct the target's scattering distribution from the echo. However, 2-D ISAR cannot represents the 3-D geometric relationship between the radar and targets, so it can only obtain the target's scattering projection on the corresponding Range-Doppler plane rather than the target's 3-D scattering distribution. To constitute a radar network, several radars should be selected from the all available radars. Because the distribution of the selected radars make an impact on the imaging performance, the distribution optimization should be considered in radar network imaging. In this paper, a novel 3-D ISAR image reconstruction method based on the optimized radar network is proposed. Firstly, the 3-D ISAR image reconstruction model is constructed by combining the projection relationship of each ISAR image and the distribution optimization. Secondly, the corresponding algorithm is proposed. With the proposed method, the optimal radar network distribution and the 3-D ISAR image can be obtained effectively. Finally, experiments demonstrate the performance of the proposed method.