A Mode Optimization Method for Vortex Electromagnetic Wave Radar Imaging

• Published in: IEEE geoscience and remote sensing letters Vol. 19; pp. 1 - 5
• Main Authors: Zhu, Yongzhong, Zhou, Yuang, Chen, Yijun, Bu, Lijun, Zhao, Hefeng
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Azimuth; Beam steering; Compressed sensing (CS); Echoes; Electromagnetic radiation; Image reconstruction; Imaging; Imaging techniques; Methods; mode optimization; Modelling; Optimization; Optimization methods; Optimization models; Radar; Radar echoes; Radar imaging; Radar scattering; Sequencing; Three dimensional models; vortex electromagnetic wave (VEMW); Vortices
• ISSN: 1545-598X; 1558-0571
• DOI: 10.1109/LGRS.2022.3177961

Since the radar echo of the space target satisfies the sparseness, the compressed sensing (CS) theory can be used to reconstruct the target information with data much lower than the Nyquist sampling rate. For the vortex electromagnetic wave (VEMW) radar, since the azimuth of the target also satisfies the sparseness, the use of CS can also significantly reduce the requirement of the azimuth resolution on the amount of mode data. Based on the abovementioned analysis, this letter proposes a CS-based VEMW radar imaging mode sequence optimization method. First, the imaging model is deduced, and the beam steering method is performed to adjust the direction of the main lobe of the VEMW in different modes, so that the target can be fully illuminated. On the basis, a sparse model of the VEMW radar is established, and the analysis shows that the essence of mode sequence optimization is to optimize the observation matrix in CS. Finally, after establishing the optimization model of the observation matrix, an optimization method is proposed to solve the model, and the 3D information of the target is reconstructed at last. Simulation experiment results prove the effectiveness of this method.