This is the authors' abstract. We don't add key points for this paper.
Combining inverse projection and vote accumulation methods, we propose a novel 3D geometric reconstruction method based on inverse synthetic aperture radar (ISAR) image sequence for triaxially stabilized space targets. Considering that the translation of a triaxially stabilized space target results in a large angular rotation of the radar line of sight (LOS) and an attitude adjustment rotation of the target itself, the projection relationship between radar imaging plane and a triaxially stabilized space target is constructed first. Subsequently, we perform an inverse projection on the dominant points extracted from each imaging plane to determine the location of the 3D candidate scatterers and assign a voting value of 1 to each position. By accumulating these vote values, we can obtain the total number of votes for the candidate scatterer position. We treat candidate 3D scatterers with a large cumulative number of votes as actual scatterers. Thus, the target 3D geometry can be obtained. Compared to traditional matrix factorization based 3D reconstruction methods, this method is more accurate and ensures that the target pose is consistent with the actual pose. At the same time, compared with 3D reconstruction methods based on energy accumulation ideas, this method produces fewer false scatterers and has higher credibility. Experimental results based on the simulated point target and electromagnetic data are presented to validate the effectiveness and robustness of the proposed method.
Answers are grounded in this paper and cite their sources.
No takes yet. Share an insight, caveat, or question.
Xu et al. (2024) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: