Compressed Sensing of 3D Marine Environment Monitoring Data Based on Spatiotemporal Correlation
| Autor: | Guosheng Rui, Wenbiao Tian, Ge Liu, Liyao Wu, Cui Tiantian, Junyi Huang |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Matrix difference equation
marine monitoring data General Computer Science Computer science three-dimensional data General Engineering Process (computing) 020206 networking & telecommunications 02 engineering and technology multiple measurement vector Correlation Matrix (mathematics) Compressed sensing Matrix group Dimension (vector space) spatio-temporal correlation 0202 electrical engineering electronic engineering information engineering Key (cryptography) 020201 artificial intelligence & image processing General Materials Science lcsh:Electrical engineering. Electronics. Nuclear engineering Algorithm lcsh:TK1-9971 measurement in groups |
| Zdroj: | IEEE Access, Vol 9, Pp 32634-32649 (2021) |
| ISSN: | 2169-3536 |
| Popis: | In the compressed sensing process of three-dimensional marine environmental monitoring data(3D-MMD), the traditional one-dimensional preprocessing methods and direct three-dimensional methods exhibit insufficient performance. In this study, we propose a novel compressed sensing observation and reconstruction method for 3D-MMD based on spatiotemporal correlation. Firstly, by analyzing the characteristics of two-dimensional expansion matrix group of 3D-MMD, we found that the expanded data in longitude dimension is more relevant. Then, according to the circular distribution of global longitude, the two-dimensional matrix sets are overlapped and grouped. The first and last matrices in the group are designated as the key matrix, and the difference matrix of adjacent matrices is calculated. Finally, the sampling rate of the key matrix and the difference matrix is allocated reasonably to achieve efficient observation and reconstruction. Theoretical analysis and simulation results showed that the proposed algorithm can greatly reduce the number of observations and relieve the pressure of system acquisition and storage while ensuring the reconstruction performance. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|