ArticleSensors (Basel, Switzerland)2018
Three-Dimensional Imaging Method for Array ISAR Based on Sparse Bayesian Inference.
Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Low-Complexity 3D InISAR Imaging Using a Compressive Hardware Device and a Single Receiver.Sensors (Basel, Switzerland) · 2022Article
- An Image Registration Method Based on Correlation Matching of Dominant Scatters for Distributed Array ISAR.Sensors (Basel, Switzerland) · 2022Article
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Authors and funding
4 authors.
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Abstract
The problem of synthesis scatterers in inverse synthetic aperture radar (ISAR) make it difficult to realize high-resolution three-dimensional (3D) imaging. Radar array provides an available solution to this problem, but the resolution is restricted by limited aperture size and number of antennas, leading to deterioration of the 3D imaging performance. To solve these problems, we propose a novel 3D imaging method with an array ISAR system based on sparse Bayesian inference. First, the 3D imaging model using a sparse linear array is introduced. Then the elastic net estimation and Bayesian information criterion are introduced to fulfill model order selection automatically. Finally, the sparse Bayesian inference is adopted to realize super-resolution imaging and to get the 3D image of target of interest. The proposed method is used to process real radar data of a Ku band array ISAR system. The results show that the proposed method can effectively solve the problem of synthesis scatterers and realize super-resolution 3D imaging, which verify the practicality of our proposed method.
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