Abstract

Due to the limited information of two-dimensional (2D) radar images, the study of three-dimensional (3D) radar image reconstruction has received significant attention. However, the target attitude obtained by the existing 3D reconstruction methods is unknown. In addition, using a single perspective, one can only get 3D reconstruction result of a simple target. For a complex target, due to occlusion and scattering characteristics, 3D reconstruction information obtained from a single perspective is limited. To tackle the above two problems, this paper proposes a new method for multi-perspective 3D reconstruction and single perspective instantaneous target attitude estimation. This method consists of three steps. First, the result of 3D reconstruction with unknown attitude is obtained by the traditional matrix factorization method. Then, in order to obtain the attitude of a target 3D reconstruction, additional constraints are added to the projection vectors which are computed from the matrix factorization method. Finally, the information from different perspectives are merged into a single layer information according to certain rules. After the information fusion, a multi-perspective 3D reconstruction structure with better visibility and more information is obtained. Simulation results have proved the effectiveness and robustness of the proposed method.

Highlights

  • Inverse synthetic aperture radar (ISAR) imaging has been widely used in military and civil areas due to day-and-night and weather-independent capability [1,2,3,4,5,6]

  • The existing 3D imaging methods can be roughly categorized into three groups based on the number of antennas: interferometric ISAR (InISAR), direct 3D ISAR imaging and 3D reconstruction, as follows: The InISAR employs at least two antennas placed in special positions [10,11,12,13,14,15,16,17,18,19,20,21]

  • The InISAR system can obtain the 3D image without prior knowledge of the target motion, it is of relatively high cost and hardware complexity for a single radar

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Summary

Introduction

Inverse synthetic aperture radar (ISAR) imaging has been widely used in military and civil areas due to day-and-night and weather-independent capability [1,2,3,4,5,6]. In [34], the multi-view radar image sequences are combined with the optical images to obtain the target 3D structure This method needs to perform orientation calibration, which is time-consuming. To reduce the computational burden of cross-range scaling, [26] performs the cross-range scaling and the matrix factorization repeatedly to achieve accurate 3D geometry reconstruction This method is only suitable for targets with linear changes in speed and the attitude of the 3D geometry reconstruction is unknown. To deal with the aforementioned problems, this paper proposes a method to perform multi-perspective 3D reconstruction and estimate the target attitude from the instantaneous 3D reconstruction result. Based on the traditional 3D reconstruction method, additional constraints are added to the projection vectors to obtain the target attitude. Equation (4) reveals the projection process from 3D space to 2D space

Traditional 3D Geometry Reconstruction Based on Factorization Method
Analysis and Estimation of 3D Reconstruction Attitude
Joint Multi-Perspective 3D Reconstruction
Target Attitude Relationship
Point Cloud Fusion
Algorithm Summation
Simulations

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