Improving RPCA-Based Clutter Suppression in GPR Detection of Antipersonnel Mines

• Published in: IEEE geoscience and remote sensing letters Vol. 14; no. 8; pp. 1338 - 1342
• Main Authors: Song, Xiaoji, Xiang, Deliang, Zhou, Kai, Su, Yi
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.08.2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Antennas; Antipersonnel mines; Clutter; Clutter suppression; Computer simulation; Contamination; Detection; Ground penetrating radar; ground-penetrating radar (GPR); Imaging techniques; Information retrieval; Land mines; landmine detection; Mathematical models; Matrix decomposition; Methods; Mines; Numerical simulations; Permits; Principal component analysis; Principal components analysis; Radar; robust principal component analysis (RPCA); Simulation; Soil contamination; Sparse matrices; System effectiveness; Target recognition

Detecting shallow buried antipersonnel mines (APMs) with a ground-penetrating radar (GPR) is a challenging task because of clutter contamination, which often obscures the APM response. In this letter, a novel method combining migration imaging with the low-rank and sparse representation method to su...