Harmonizing Deep-Sea Geomagnetic Sampling and Aeronautical Channel Modeling through Compressed Sensing
Keywords:
Compressed Sensing, Geomagnetic Mapping, Aeronautical Communications, Sparse Signal ProcessingAbstract
The relentless demand for high-fidelity data acquisition in extreme operational environments presents substantial engineering and theoretical challenges. Deep-sea geomagnetic sampling and aeronautical channel modeling are two distinct domains that share fundamental constraints regarding energy availability, data transmission bandwidth, and sensor deployment costs. This paper investigates the application of compressed sensing as a unifying signal processing paradigm to overcome the limitations of traditional Nyquist-Shannon sampling techniques in these dual contexts. By exploiting the inherent sparsity present in both deep-sea magnetic field anomalies and aeronautical delay-Doppler communication channels, compressed sensing enables accurate signal reconstruction from significantly fewer measurements. The research provides a comprehensive theoretical framework and outlines specialized measurement matrices and reconstruction algorithms tailored to the physical realities of oceanographic and aerospace environments. Extensive analytical evaluations demonstrate that the proposed compressed sensing methodologies substantially reduce the power consumption of autonomous underwater vehicles while simultaneously enhancing the resolution of highly mobile aeronautical communication links. The findings establish a cohesive academic foundation for deploying sub-Nyquist sampling strategies across radically different physical mediums, ultimately advancing the design of next-generation remote sensing and communication systems.
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