Multistatic Data Matrix Mixed Eigenvector Processing for Time-Reversal Imaging

• Published in: IEEE geoscience and remote sensing letters Vol. 22; pp. 1 - 5
• Main Authors: Zhou, Qiping, Teixeira, Fernando L.
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2025; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Antenna arrays; Eigenvalues and eigenfunctions; Eigenvectors; Electromagnetic scattering; Geoscience and remote sensing; Image reconstruction; Image resolution; Imaging; Microwave imaging; Multiple signal classification; Noise; Random media; selective focusing; Signal classification; Subspace methods; target localization; Time-domain analysis; time-reversal imaging
• ISSN: 1545-598X; 1558-0571
• DOI: 10.1109/LGRS.2024.3514535

In this work, a new array imaging algorithm is proposed that combines the relative advantages of two widely used subspace methods for microwave imaging: multiple signal classification (MUSIC) and time-reversal operator decomposition (DORT, under its French acronym). For the examples considered, the proposed algorithm yields a better imaging performance (in terms of resolution and selective focusing ability) than DORT and an imaging performance similar to MUSIC. At the same time, it provides a reduced computational burden of about 20% relative to that of MUSIC and only a slight increase relative to DORT.